Re-admission patterns in England and the Netherlands: a comparison based on administrative data of all hospitals.

BACKGROUND: Examining variation in patterns of re-admissions between countries can be valuable for mutual learning in order to reduce unnecessary re-admissions. The aim of this study was to compare re-admission rates and reasons for re-admissions between England and the Netherlands. METHODS: We used data from 85 Dutch hospitals (1 355 947 admissions) and 451 English hospitals (5 260 227 admissions) in 2014 (96% of all Dutch hospitals and 100% of all English NHS hospitals). Re-admission data from England and the Netherlands were compared for all hospital patients and for specific diagnosis groups: pneumonia, urinary tract infection, chronic obstructive pulmonary disease, coronary atherosclerosis, biliary tract disease, hip fracture and acute myocardial infarction. Re-admissions were categorized using a classification system developed on administrative data. The classification distinguishes between potentially preventable re-admissions and other reasons for re-admission. RESULTS: England had a higher 30-day re-admission rate (adjusted for age and gender) compared to the Netherlands: 11.17% (95% CI 11.14-11.20%) vs. 9.83% (95% CI 9.77-9.88%). The main differences appeared to be in re-admissions for the elderly (England 17.2% vs. the Netherlands 10.0%) and in emergency re-admissions (England 85.3% of all 30-day re-admissions vs. the Netherlands 66.8%). In the Netherlands, however, more emergency re-admissions were classified as potentially preventable compared to England (33.8% vs. 28.8%). CONCLUSIONS: The differences found between England and the Netherlands indicate opportunities to reduce unnecessary re-admissions. For England this concerns more expanded palliative care, integrated social care and reduction of waiting times. In the Netherlands, the use of treatment plans for daily life could be increased.

How to identify potentially preventable readmissions by classifying them using a national administrative database.

IMPORTANCE: Hospital readmissions are being used increasingly as an indicator of quality of care. However, it remains difficult to identify potentially preventable readmissions. OBJECTIVES: To evaluate the identification of potentially preventable hospital readmissions by using a classification of readmissions based on administrative data. DESIGN AND SETTING: We classified a random sample of 455 readmissions to a Dutch university hospital in 2014 using administrative data. We compared these results to a classification based on reviewing the medical records of these readmissions to evaluate the accuracy of classification by administrative data. MAIN OUTCOME MEASURES: Frequencies of categories of readmissions based on reviewing records versus those based on administrative data. Cohen's kappa for the agreement between both methods. The sensitivity and specificity of the identification of potentially preventable readmissions with classification by administrative data. RESULTS: Reviewing the medical records of acute readmissions resulted in 28.5% of the records being classified as potentially preventable. With administrative data this was 44.1%. There was slight agreement between both methods: ƙ 0.08 (95% CI: 0.02-0.15, P < 0.05). The sensitivity of the classification of potentially preventable readmissions by administrative data was 63.1% and the specificity was 63.5%. CONCLUSIONS: This explorative study demonstrated differences between categorizing readmissions based on reviewing records compared to using administrative data. Therefore, this tool can only be used in practice with great caution. It is not suitable for penalizing hospitals based on their number of potentially preventable readmissions. However, hospitals might use this classification as a screening tool to identify potentially preventable readmissions more efficiently.