Substituting inpatient for outpatient care: what is the impact on hospital costs and efficiency?

How to improve efficiency in cancer care: dimensions, methods, and areas of evaluation

Efficiency in healthcare is crucial since available resources are scarce, and the opportunity cost of an inefficient allocation is measured in health outcomes foregone. This is particularly relevant for cancer. The aim of this paper was to gain a comprehensive overview of how efficiency in cancer care is defined, and what the indicators, different methods, perspectives, and areas of evaluation are, to provide recommendations on the areas and dimensions where efficiency can be improved. METHODS: A comprehensive scoping literature review was performed searching four databases. Studies published between 2000-2021 were included if they described experiences and cases of efficiency in cancer care or methods to evaluate efficiency. The results of the literature review were then discussed during two rounds of online consultation with a panel of 15 external experts invited to provide their insights and comments to deliberate policy recommendations. RESULTS: 46 papers met the inclusion criteria. Based on the papers retrieved we have identified six areas for achieving efficiency gains throughout the entire care pathway and, for each area of efficiency, we have categorized the methods and outcome used to measure efficiency gain CONCLUSION: This is the first attempt to systematize a scattered body of literature on how to improve efficiency in cancer care and identify key areas to improve it. Based on the findings of the literature review and on the opinion of the experts involved in the consultation, we propose seven recommendations that are intended to improve efficiency in cancer care throughout the care pathway.

Costs of polish county hospitals-A behavioral panel function

In the paper the costs of Polish county hospitals in 2015-2018 are studied using behavioral cost function. The set of variables combines hospitals' characteristics which may determine their level of costs, such as the form of ownership, bed turnover rate, number of patient-days and share of beds in emergency department with environment characteristics which may influence both outsourcing costs and patients' health. In 2017 the system of basic hospital service provision (hospital network) was introduced in Poland. Dummy variables included in the model represent the category of hospital in the system. The results show that the costs may be described using fixed effect panel model. Positive impact of percentage of emergency department patients transferred to other departments and of wages is found. Higher ratio of residents and interns to doctors is found to decrease costs. Dummy variable for the period after the introduction of hospital network assumed a negative sign with costs, but the parameter remained insignificant.

What Really Matters? Organizational Versus Regional Determinants of Hospitals Providing Medical Service Centres

By adding medical service centres (MSCs) to their range of services, hospitals can participate in the outpatient sector. The aim of the MSC guideline (2004) was to ensure high quality health care in rural areas. It is unknown if organizational or regional factors influence hospitals providing services via MSCs. Our analyses focus on the identification of factors that explain the operation of an MSC by hospitals. The data are based on the mandatory structured quality reports of German hospitals (n = 1,605). These organizational data (teaching status, size and ownership) are supplemented by settlement structure and contextual data (e.g., location, doctor density). We estimated a cross-sectional multilevel logistic regression model to identify determinants of hospitals operating MSCs. In 2017, 27% of 1,605 hospitals had one or more MSCs. On an organizational level, for-profit ownership (-) and the number of beds (+) were significant determinants of providing MSCs. The analyses show that the interaction between settlement structure and ownership has an influence on the operation of an MSC. Organizational factors determine the provision of MSCs, with regional determinants playing a role as well. This indicates that hospital behaviour is difficult to predict and that individual factors shape both profit orientation and responsibility for sufficient health care in the region.

Hospital productivity bias when not adjusting for cost heterogeneity: The case of Spain

This research quantifies the bias caused in hospital productivity measurements when cost heterogeneity is not considered. A multi-output stochastic cost frontier under a normalised translog specification is used to approximate the structure of technology of a sample of public general hospitals in Spain during the period 2002–2009. To control for observable heterogeneity in costs, a set of variables related to hospital characteristics are included in the cost frontier specification (i.e., hospital complexity, degree of specialisation, availability of outpatient clinics, variety of high-technology equipment available, teaching activity and quality of care), whereas unobservable heterogeneity is accounted for by means of individual dummy variables. A measure of hospitals’ cost efficiency is first obtained, and the analysis is then completed by measuring and decomposing the total factor productivity index (TFP-I) change. Findings reveal that controlling for heterogeneity decreases total productivity from an annual average rate of 0.028% to 1.330%, mainly driven by the negative contribution of the cost efficiency change component. Hence, a bias of 1.303 percentage points in the overall TFP-I is found as consequence of not controlling for heterogeneity. In addition to this, if heterogeneity factors are not accounted for, the mean cost efficiency index during the period analysed is 0.730, figure that increases up to 0.974 if heterogeneity is considered. Hence, the omission of heterogeneity leads to a bias of 24.4 percentage points in the mean cost efficiency. Therefore, not adjusting for heterogeneity in costs gives rise to distorted measurements of hospital productivity, as well as distortions in the contribution of each of its components, which may lead to the adoption of inadequate policies and decisions on resource allocation.

Outpatient Treatment Based on Self-Management Strategies for Chronic Drooling in Two Children

Drooling is a distressing condition, which is often caused by reduced oral motor control associated with a neurological disorder. It has significant medical, practical and psychosocial impact on children or youth and their families. Therefore, treatment is necessary. Although behavioural therapy for drooling shows promising results, it is generally time- and cost-intensive. For this reason, alternative ways to provide behavioural treatment for chronic drooling need to be explored. In a pair of case studies, the feasibility and potential of an outpatient variant of a behavioural treatment programme for drooling based on self-management strategies was researched with two children with oral motor difficulties. In a three week programme, these children were taught to perform a self-management routine in order to achieve saliva control during regular visits to the child rehabilitation centre. In addition, their parents and teachers were taught to prompt the self-management routine and instructed to provide additional practice at home and at school. In doing so, they were offered support by means of telehealth and personal contact. At the end of the treatment programme, both children showed a significant decrease in drooling severity. Their parents and teachers were satisfied with the treatment effect. Although the present treatment programme showed promising results, further adaptions are necessary to make the treatment programme more widely accessible.

Assessing physician productivity following Norwegian hospital reform: A panel and data envelopment analysis

BACKGROUND

Although health care reforms may improve efficiency at the macro level, less is known regarding their effects on the utilization of health care personnel. Following the 2002 Norwegian hospital reform, we studied the productivity of the physician workforce and the effect of personnel mix on this measure in all nineteen Norwegian hospitals from 2001 to 2013.

METHODS

We used panel analysis and non-parametric data envelopment analysis (DEA) to study physician productivity defined as patient treatments per full-time equivalent (FTE) physician. Resource variables were FTE and salary costs of physicians, nurses, secretaries, and other personnel. Patient metrics were number of patients treated by hospitalization, daycare, and outpatient treatments, as well as corresponding diagnosis-related group (DRG) scores accounting for differences in patient mix. Research publications and the fraction of residents/FTE physicians were used as proxies for research and physician training.

RESULTS

The number of patients treated increased by 47% and the DRG scores by 35%, but there were no significant increases in any of the activity measures per FTE physician. Total DRG per FTE physician declined by 6% (p < 0.05). In the panel analysis, more nurses and secretaries per FTE physician correlated positively with physician productivity, whereas physician salary was neutral. In 2013, there was a 12%-80% difference between the hospitals with the highest and lowest physician productivity in the differing treatment modalities. In the DEA, cost efficiency did not change in the study period, but allocative efficiency decreased significantly. Bootstrapped estimates indicated that the use of physicians was too high and the use of auxiliary nurses and secretaries was too low.

CONCLUSIONS

Our measures of physician productivity declined from 2001 to 2013. More support staff was a significant variable for predicting physician productivity. Personnel mix developments in the study period were unfavorable with respect to physician productivity.

A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix : How to Evaluate When There is Not DRGs?

The public health system has restricted economic resources. Because of that, it is necessary to know how the resources are being used and if they are properly distributed. Several works have applied classical approaches based in Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) for this purpose. However, if we have hospitals with different casemix, this is not the best approach. In order to avoid biases in the comparisons, other works have recommended the use of hospital production data corrected by the weights from Diagnosis Related Groups (DRGs), to adjust the casemix of hospitals. However, not all countries have this tool fully implemented, which limits the efficiency evaluation. This paper proposes a new approach for evaluating the efficiency of hospitals. It uses a graph-based clustering algorithm to find groups of hospitals that have similar production profiles. Then, DEA is used to evaluate the technical efficiency of each group. The proposed approach is tested using the production data from 2014 of 193 Chilean public hospitals. The results allowed to identify different performance profiles of each group, that differs from other studies that employs data from partially implemented DRGs. Our results are able to deliver a better description of the resource management of the different groups of hospitals. We have created a website with the results ( bioinformatic.diinf.usach.cl/publichealth ). Data can be requested to the authors.

The excess health care costs of KardioPro, an integrated care program for coronary heart disease prevention

Coronary heart disease (CHD) is a major cause of death and important driver of health care costs. Recent German health care reforms have promoted integrated care contracts allowing statutory health insurance providers more room to organize health care provision. One provider offers KardioPro, an integrated primary care-based CHD prevention program. As insurance providers should be aware of the financial consequences when developing optional programs, this study aims to analyze the costs associated with KardioPro participation. 13,264 KardioPro participants were compared with a propensity score-matched control group. Post-enrollment health care costs were calculated based on routine data over a follow-up period of up to 4 years. For those people who incurred costs, KardioPro participation was significantly associated with increased physician costs (by 33%), reduced hospital costs (by 19%), and reduced pharmaceutical costs (by 16%). Overall costs were increased by 4%, but this was not significant. Total excess costs per observation year were €131 per person (95% confidence interval: [€-36.5; €296]). Overall, KardioPro likely affected treatment as the program increased costs of physician services and reduced costs of hospital services. Further effects of substituting potential inpatient care with increased outpatient care might become fully apparent only over a longer time horizon.

Individual and hospital-specific factors influencing medical graduates' time to medical specialization

Previous studies of gender differences in relation to medical specialization have focused more on social variables than hospital-specific factors. In a multivariate analysis with extended Cox regression, we used register data for socio-demographic variables (gender, family and having a child born during the study period) together with hospital-specific variables (the amount of supervision available, efficiency pressure and the type of teaching hospital) to study the concurrent effect of these variables on specialty qualification among all 2474 Norwegian residents who began specialization in 1999-2001. We followed the residents until 2010. A lower proportion of women qualified for a specialty in the study period (67.9% compared with 78.7% of men, p < 0.001), and they took on average six months longer than men did to complete the specialization qualification (p < 0.01). Fewer women than men entered specialties providing emergency services and those with longer working hours, and women worked shorter hours than men in all specialties. Hospital factors were significant predictors for the timely attainment of specialization: working at university hospitals (regional) or central hospitals was associated with a reduction in the time taken to complete the specialization, whereas an increased patient load and less supervision had the opposite effect. Multivariate analysis showed that the smaller proportion of women who qualified for a specialty was explained principally by childbirth and by the number of children aged under 18 years.