Patterns of nonemergent visits to different healthcare facilities on the same day: a nationwide analysis in Taiwan

Incidence and risk of dialysis therapy within 30 days after contrast enhanced computed tomography in patients coded with chronic kidney disease: a nation-wide, population-based study

Background

Patients with chronic kidney disease (CKD) are considered at risk of contrast-induced acute kidney injury and possible subsequent need for dialysis therapy. Computed tomography (CT) is the most commonly performed examination requiring intravenous iodinated contrast media (ICM) injection. The actual risk of dialysis in CKD patients undergoing CT with ICM remains controversial. Furthermore, it is also uncertain whether these at-risk patients can be identified by means of administrative data. Our study is conducted in order to determine the incidence and risk of dialysis within 30 days after undergoing contrast enhanced CT in CKD coded patients.

Methods

This longitudinal, nation-wide, populated-based study is carried out by analyzing the Taiwan National Health Insurance Research Database retrospectively. Patients coded under the diagnosis of CKD who underwent CT are identified within randomly selected one million subjects of the database. From January 2012 to December 2013, 487 patients had undergone CT with ICM. A total of 924 patients who underwent CT without ICM are selected as the control group. Patients with advanced CKD or intensive care unit (ICU) admissions are assigned to the subgroups for analysis. The primary outcome is measured by dialysis events within 30 days after undergoing CT scans. The cumulative incidence is assessed by the Kaplan–Meier method and log-rank test. The risk of 30-day dialysis relative to the control group is analyzed by the Cox proportional hazards model after adjusting for age, sex, and baseline comorbidities.

Results

The numbers and percentages of dialysis events within 30 days after undergoing CT scans are 20 (4.1%) in the CT with ICM group and 66 (7.1%) in the CT without ICM group (p = 0.03). However, the adjusted hazard ratio (aHR) for 30-day dialysis was 0.84 (95% CI [0.46–1.54], p = 0.57), which is statistically non-significant. In both advanced CKD and ICU admission subgroups, there are also no significant differences in 30-day dialysis risks with the aHR of 1.12 (95% CI [0.38–3.33], p = 0.83) and 0.95 (95% CI [0.44–2.05], p = 0.90), respectively.

Conclusions

Within 30 days of receiving contrast-enhanced CT scans, 4.1% of CKD coded patients required dialysis, which appear to be lower compared with subjects who received non-contrast CT scans. However, no statistically significant difference is observed after adjustments are made for other baseline conditions. Thereby, the application of administrative data to identify patients with CKD cannot be viewed as a risk factor for the necessity to undergo dialysis within 30 days of receiving contrast-enhanced CT scans.

Characteristics of doctor-shoppers: a systematic literature review

Objective: Doctor-shopping has significant consequences for patients and payers and can indicate misuse of drugs, polypharmacy, less continuity of care, and increased medical expenses. This study reviewed the literature describing doctor-shoppers in the adult population. Methods: A systematic literature review was performed in PubMed and supplemented by a Google search of grey literature. Overall, 2885 records were identified; 43 papers served as a source of definition of a doctor-shopper, disease, treatment, patient characteristics, patient special needs, country. Results: Definitions of doctor-shopping were heterogeneous. Overall, 40% of studies examined the use of opioids, antidepressants, or psychoactive drugs, while the others focused on chronic or frequent diseases. Most studies were conducted in countries with easy access to healthcare resources (USA, France, Taiwan, Hong Kong). The prevalence of doctor-shopping ranged from 0.5% among opioid users in the USA to 25% of patients registered at general practices in Japan. Comorbidities, active substance abuse, greater distance from healthcare facility, younger age, longer disease and poor patient satisfaction increased doctor-shopping. Conclusions: Knowing the characteristics of doctor-shoppers may help identify such patients and reduce the associated waste of medical resources, but concerns about the misuse of drugs or healthcare resources should not prevent proper disease management.