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1.  Variation in Hospital Length of Stay: Do Physicians Adapt Their Length of Stay Decisions to What Is Usual in the Hospital Where They Work? 
Health Services Research  2006;41(2):374-394.
Objective
To test the hypothesis that physicians who work in different hospitals adapt their length of stay decisions to what is usual in the hospital under consideration.
Data Sources
Secondary data were used, originating from the Statewide Planning and Research Cooperative System (SPARCS). SPARCS is a major management tool for assisting hospitals, agencies, and health care organizations with decision making in relation to financial planning and monitoring of inpatient and ambulatory surgery services and costs in New York state.
Study Design
Data on length of stay for surgical interventions and medical conditions (a total of seven diagnosis-related groups [DRGs]) were studied, to find out whether there is more variation between than within hospitals. Data (1999, 2000, and 2001) from all hospitals in New York state were used. The study examined physicians practicing in one hospital and physicians practicing in more than one hospital, to determine whether average length of stay differs according to the hospital of practice. Multilevel models were used to determine variation between and within hospitals. A t-test was used to test whether length of stay for patients of each multihospital physician differed from the average length of stay in each of the two hospitals.
Principal Findings
There is significantly (p<.05) more variation between than within hospitals in most of the study populations. Physicians working in two hospitals had patient lengths of stay comparable with the usual practice in the hospital where the procedure was performed. The proportion of physicians working in one hospital did not have a consistent effect for all DRGs on the variation within hospitals.
Conclusion
Physicians adapt to their colleagues or to the managerial demands of the particular hospital in which they work. The hospital and broader work environment should be taken into account when developing effective interventions to reduce variation in medical practice.
doi:10.1111/j.1475-6773.2005.00486.x
PMCID: PMC1702523  PMID: 16584454
Length of stay; variation; hospitals; multihospital physicians
2.  Labour intensity of guidelines may have a greater effect on adherence than GPs' workload 
BMC Family Practice  2009;10:74.
Background
Physicians' heavy workload is often thought to jeopardise the quality of care and to be a barrier to improving quality. The relationship between these has, however, rarely been investigated. In this study quality of care is defined as care 'in accordance with professional guidelines'. In this study we investigated whether GPs with a higher workload adhere less to guidelines than those with a lower workload and whether guideline recommendations that require a greater time investment are less adhered to than those that can save time.
Methods
Data were used from the Second Dutch National survey of General Practice (DNSGP-2). This nationwide study was carried out between April 2000 and January 2002.
A multilevel logistic-regression analysis was conducted of 170,677 decisions made by GPs, referring to 41 Guideline Adherence Indicators (GAIs), which were derived from 32 different guidelines. Data were used from 130 GPs, working in 83 practices with 98,577 patients. GP-characteristics as well as guideline characteristics were used as independent variables. Measures include workload (number of contacts), hours spent on continuing medical education, satisfaction with available time, practice characteristics and patient characteristics. Outcome measure is an indicator score, which is 1 when a decision is in accordance with professional guidelines or 0 when the decision deviates from guidelines.
Results
On average, 66% of the decisions GPs made were in accordance with guidelines. No relationship was found between the objective workload of GPs and their adherence to guidelines. Subjective workload (measured on a five point scale) was negatively related to guideline adherence (OR = 0.95). After controlling for all other variables, the variation between GPs in adherence to guideline recommendations showed a range of less than 10%.
84% of the variation in guideline adherence was located at the GAI-level. Which means that the differences in adherence levels between guidelines are much larger than differences between GPs. Guideline recommendations that require an extra time investment during the same consultation are significantly less adhered to: (OR = 0.46), while those that can save time have much higher adherence levels: OR = 1.55). Recommendations that reduce the likelihood of a follow-up consultation for the same problem are also more often adhered to compared to those that have no influence on this (OR = 3.13).
Conclusion
No significant relationship was found between the objective workload of GPs and adherence to guidelines. However, guideline recommendations that require an extra time investment are significantly less well adhered to while those that can save time are significantly more often adhered to.
doi:10.1186/1471-2296-10-74
PMCID: PMC2791751  PMID: 19943953
3.  Do list size and remuneration affect GPs' decisions about how they provide consultations? 
Background
Doctors' professional behaviour is influenced by the way they are paid. When GPs are paid per item, i.e., on a fee-for-service basis (FFS), there is a clear relationship between workload and income: more work means more money. In the case of capitation based payment, workload is not directly linked to income since the fees per patient are fixed. In this study list size was considered as an indicator for workload and we investigated how list size and remuneration affect GP decisions about how they provide consultations. The main objectives of this study were to investigate a) how list size is related to consultation length, waiting time to get an appointment, and the likelihood that GPs conduct home visits and b) to what extent the relationships between list size and these three variables are affected by remuneration.
Methods
List size was used because this is an important determinant of objective workload. List size was corrected for number of older patients and patients who lived in deprived areas. We focussed on three dependent variables that we expected to be related to remuneration and list size: consultation length; waiting time to get an appointment; and home visits. Data were derived from the second Dutch National Survey of General Practice (DNSGP-2), carried out between 2000 and 2002. The data were collected using electronic medical records, videotaped consultations and postal surveys. Multilevel regression analyses were performed to assess the hypothesized relationships.
Results
Our results indicate that list size is negatively related to consultation length, especially among GPs with relatively large lists. A correlation between list size and waiting time to get an appointment, and a correlation between list size and the likelihood of a home visit were only found for GPs with small practices. These correlations are modified by the proportion of patients for whom GPs receive capitation fees. Waiting times to get an appointment tend to become shorter with increasing patient lists when there is a larger capitation percentage. The likelihood that GPs will conduct home visit rises with increasing patient lists when the capitation percentage is small.
Conclusion
Remuneration appears to affect GPs' decisions about how they provide consultations, especially among GPs with relatively small patient lists. This role is, however, small compared to other factors such as patient characteristics.
doi:10.1186/1472-6963-9-39
PMCID: PMC2654894  PMID: 19245685
4.  Do decision support systems influence variation in prescription? 
Background
Translating scientific evidence into daily practice is problematic. All kinds of intervention strategies, using educational and/or directive strategies, aimed at modifying behavior, have evolved, but have been found only partially successful. In this article the focus is on (computerized) decision support systems (DSSs). DSSs intervene in physicians' daily routine, as opposed to interventions that aim at influencing knowledge in order to change behavior. We examined whether general practitioners (GPs) are prescribing in accordance with the advice given by the DSS and whether there is less variation in prescription when the DSS is used.
Methods
Data were used from the Second Dutch National Survey of General Practice (DNSGP2), collected in 2001. A total of 82 diagnoses, 749811 contacts, 133 physicians, and 85 practices was included in the analyses. GPs using the DSS daily were compared to GPs who do not use the DSS. Multilevel analyses were used to analyse the data. Two outcome measures were chosen: whether prescription was in accordance with the advice of the DSS or not, and a measure of concentration, the Herfindahl-Hirschman Index (HHI).
Results
GPs who use the DSS daily prescribe more according to the advice given in the DSS than GPs who do not use the DSS. Contradictory to our expectation there was no significant difference between the HHIs for both groups: variation in prescription was comparable.
Conclusion
We studied the use of a DSS for drug prescribing in general practice in the Netherlands. The DSS is based on guidelines developed by the Dutch College of General Practitioners and implemented in the Electronic Medical Systems of the GPs. GPs using the DSS more often prescribe in accordance with the advice given in the DSS compared to GPs not using the DSS. This finding, however, did not mean that variation is lower; variation is the same for GPs using and for GPs not using a DSS. Implications of the study are that DSSs can be used to implement guidelines, but that it should not be expected that variation is limited.
doi:10.1186/1472-6963-9-20
PMCID: PMC2662826  PMID: 19183464
5.  Does managed care make a difference? Physicians' length of stay decisions under managed and non-managed care 
Background
In this study we examined the influence of type of insurance and the influence of managed care in particular, on the length of stay decisions physicians make and on variation in medical practice.
Methods
We studied lengths of stay for comparable patients who are insured under managed or non-managed care plans. Seven Diagnosis Related Groups were chosen, two medical (COPD and CHF), one surgical (hip replacement) and four obstetrical (hysterectomy with and without complications and Cesarean section with and without complications). The 1999, 2000 and 2001 – data from hospitals in New York State were used and analyzed with multilevel analysis.
Results
Average length of stay does not differ between managed and non-managed care patients. Less variation was found for managed care patients. In both groups, the variation was smaller for DRGs that are easy to standardize than for other DRGs.
Conclusion
Type of insurance does not affect length of stay. An explanation might be that hospitals have a general policy concerning length of stay, independent of the type of insurance of the patient.
doi:10.1186/1472-6963-4-3
PMCID: PMC368442  PMID: 15028122
6.  QUALICOPC, a multi-country study evaluating quality, costs and equity in primary care 
BMC Family Practice  2011;12:115.
Background
The QUALICOPC (Quality and Costs of Primary Care in Europe) study aims to evaluate the performance of primary care systems in Europe in terms of quality, equity and costs. The study will provide an answer to the question what strong primary care systems entail and which effects primary care systems have on the performance of health care systems. QUALICOPC is funded by the European Commission under the "Seventh Framework Programme". In this article the background and design of the QUALICOPC study is described.
Methods/design
QUALICOPC started in 2010 and will run until 2013. Data will be collected in 31 European countries (27 EU countries, Iceland, Norway, Switzerland and Turkey) and in Australia, Israel and New Zealand. This study uses a three level approach of data collection: the system, practice and patient. Surveys will be held among general practitioners (GPs) and their patients, providing evidence at the process and outcome level of primary care. These surveys aim to gain insight in the professional behaviour of GPs and the expectations and actions of their patients. An important aspect of this study is that each patient's questionnaire can be linked to their own GP's questionnaire. To gather data at the structure or national level, the study will use existing data sources such as the System of Health Accounts and the Primary Health Care Activity Monitor Europe (PHAMEU) database. Analyses of the data will be performed using multilevel models.
Discussion
By its design, in which different data sources are combined for comprehensive analyses, QUALICOPC will advance the state of the art in primary care research and contribute to the discussion on the merit of strengthening primary care systems and to evidence based health policy development.
doi:10.1186/1471-2296-12-115
PMCID: PMC3206822  PMID: 22014310

Results 1-6 (6)