Day Case Surgery Turns into Unplanned Overnight Stays
- 1 Basic Facts
- 2 Brief overview of the measure
- 3 Application and interpretation of the measure
- 4 Calculation of the measure
- 5 Appraisal of the measure
- 6 Other items
- 7 Owner details
Stage of development
Potential or current usage
This measure is intended to unplanned overnight stays as a potential marker of quality and efficiency issues.
Brief overview of the measure
This indicator measures the proportion of planned day case admissions which turn into unplanned overnight stays.
Rationale for selection
Day case overstays are an outcome and efficiency measure of secondary care at a surgical department level. An unplanned overnight stay from a day case is always a diversion from the ‘planned approach to care’, even if we do not know the cause of why the extended stay occurred (and there may be a very good clinical reason for the change). While the measure reflects a change in plan (a cause of inconvenience to patients, disruption to planned hospital flow, etc) it is an area where both cause and proper response is uncertain. It may reflect an adverse incident in a procedure, unrealistic assessment about what may be treated as a day case or some other local factor. This makes it a rare sort of indicator that both raises questions and provides an assessment of performance, with both quality and efficiency dimensions.
Type of measure
Domain(s) of quality
Application and interpretation of the measure
Stated intent of the measure
To explore aspects of effectiveness and efficiency in surgery.
Caveats - Considerations
This measure does not identify the reasons for an overstay and there may be very legitimate clinical reasons for keeping patients overnight. Hence the results need to be interpreted with caution. The measure may also be susceptible to variation in results between DHBs in relation to demographic or geographic factors (for example, in rural settings a potentially longer distance to hospital may affect ability to travel within the same day). As such results should be presented at a national level)
Level of health care delivery/setting
This indicator is inclusive of all age ranges, ethnicities and genders.
Stratification by vulnerable populations
Stratification by ethnicity and socio economic status is useful.
Possible sources of bias or confounding
Includes practitioner, organisational and patient factors e.g. demography, case mix, compliance that need to be allowed for when interpreting results.
Calculation of the measure
Output of calculation
Percentage of planned day case admissions which turn into overnight stays.
Admissions with a planned day case code where LOS > 0, (options for how classified: shown by specialty, for a range of day case marker procedures – e.g. cataract, arthroscopy?, using a casemix standardiser)
All admissions with a planned day case code (would need to be stratified as above)
Criteria/standard for optimal performance
Defines what is counted or measured to draw inferences about quality of care and the required level of performance on a measure which suggests optimal quality.
Method of extraction
Describes the source of the required data, and any challenges identified For example, for practice level indicators this may be the practice management system. For peer review/professional development purposes, the data source may be the patient record, utilising manual searches. For indicators with a higher level of focus, aggregated data at organisational levels or national data warehouses may provide data.
Key issues and challenges for data management
There may be an issue of geographic disparity of behaviours (e.g. a need to reflect different practice in very rural DHBs). It may also help to contextualise this indicator with overall day case rates.
Appraisal of the measure
Availability of evidence to support application of the measure
The measure has been developed or endorsed by an organization that promotes rigorous development and use of clinical performance measures (at an international, national, regional or local level)., The measure has been developed or endorsed by an organisation seeking to improve clinical effectiveness as part of a continuous quality improvement cycle (at an international, national, regional or local level).
Evidence of feasibility and reliability of implementation
Reliability - The measure has been demonstrated to be reliable (i.e. free from random error)., Interpretation - The measure allows unambiguous interpretation of better or worse performance., Data extraction - Data collection specifications for the measure are well defined., Data sources - Required data elements for the measure can be obtained from existing data sources., Availability of data - Required data elements for the measure can be gathered during routine practice activities, IT software - Existing IT software is sufficient for data collection., Validity - The measure has been demonstrated to be valid (i.e. it measures what it purports to).
Date of entry to library
Owner (Organisation name)
Health Quality and Safety Commission
Owner (Email contact)
Creator (Organisation name)
Health Quality and Safety Commission
Creator (Email contact)