emergency bed days in 12/13. Yet we know that between 20% and 30% of hospital admissions in this group could be prevented by proactive case finding, frailty assessment, care planning and use of services outside of hospital (Mytton et al 2012). The problem we face is that people with frailty are currently either not reliably identified or identified only when advanced frailty has developed. This to missed opportunities to mitigate the preventative components of frailty, to instigate proactive care models such as personalised care and support planning, and/or target geriatric resources. A clinical record of a representative sample of patients aged 75 and over who had a Data source frailty syndrome (see further guidance). Existing GP Practice Read Codes are available to people diagnosed with frailty. ‘flag’ This information would contribute to case finding systems and care planning for practice population at risk of unplanned admission. Quarterly Frequency of data collection Provider Organisation responsible for data collection Quarterly Frequency of reporting to commissioner Q1 2016/17 Baseline period/date To be determined by baseline audit Baseline Q4 2016/17 Final indicator period/date (on which payment is based) The indicator values for payment are to be agreed locally, and will represent an Final indicator value (payment achievable but stretching level of improvement from the baseline to what should be 95% threshold) or above achievement of each of the indicators.
emergency bed days in 12/13. Yet we know that between 20% and 30% of hospital admissions in this group could be prevented by proactive case finding, frailty assessment, care planning and use of services outside of hospital (Mytton et al 2012). The problem we face is that people with frailty are currently either not reliably identified or identified only when advanced frailty has developed. This to missed opportunities to mitigate the preventative components of frailty, to instigate proactive care models such as personalised care and support planning, and/or target geriatric resources. Data source A clinical record of a representative sample of patients aged 75 and over who had a frailty syndrome (see further guidance). Existing GP Practice Read Codes are available to ‘flag’ people diagnosed with frailty. This information would contribute to case finding systems and care planning for practice population at risk of unplanned admission. Frequency of data collection Quarterly Organisation responsible for data collection Provider Frequency of reporting to commissioner Quarterly Baseline period/date Q1 2016/17 Baseline To be determined by baseline audit Final indicator period/date (on which payment is based) Q4 2016/17 Final indicator value (payment threshold) The indicator values for payment are to be agreed locally, and will represent an achievable but stretching level of improvement from the baseline to what should be 95% or above achievement of each of the indicators.
cquin-lcl-physcl-hlth-indictrs-v2.docx