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Cost per day for occupied beds in various Hospital Departments

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WRITTEN QUESTION TO THE MINISTER FOR HEALTH AND SOCIAL SERVICES BY SENATOR S.C. FERGUSON

ANSWER TO BE TABLED ON TUESDAY 26th JUNE 2012

Question

Would the Minister provide Members with the annual figures for the past 10 years of the average cost per day of an occupied bed (identifying the costs included in the calculation) and average occupancy rates and average length of stay in the following units –

Surgery

Medicine

Maternity

Rehabilitation

Mental Health Acute Mental Health Long Term.

Answer

1: Average cost per day of an occupied bed

The information required to answer this Question is not been collected routinely.

Different levels of staffing are required for intensive care, maternity care, high dependency care, acute care, mental health care, residential care and nursing care, so all these beds have very different costs. In addition lower occupancy rates are required for unscheduled care as unscheduled care bed capacity must be available to deal with the variability of emergency demand. This also affects bed cost.

That said analysis based on data from 2010 conducted by KPMG in preparation for the HSSD Green estimated that the average cost per bed night was £235, based on direct costs of £1.7M in 2010 for a 20 bed ward. This does not include indirect costs for example; building and equipment costs.

2. Average Occupancy Rates and Average Length of Stay

HSSD cannot provide data in the format requested for the following reasons:

  • it has not been collected routinely for rehabilitation, mental health acute and mental health long term;
  • data collected prior to 2011, when HSSD implemented its new TrakCare, is not sufficiently robust and cannot be readily analysed, hence KPMG focused on 2010 only. The 2010 data alone required significant  analysis  from  varying  information sources  plus,  prior  to that analysis being undertaken a bespoke data cleansing exercise was required in respect of clinical coding in order to improve accuracy;
  • the data sets collected since the introduction of TrakCare are still in the process of being refined and hence do not lend readily themselves to this non-standard analysis.

HSSD has been very explicit about the requirement to invest in improved data and informatics; hence it is a key cross-cutting work steam in the White Paper.

Data for Medicine division and Surgery division has however been included in the States of Jersey Annual Performance Report, and is collated below from 2005 to 2009. In considering this data it is essential to understand that:

  • as detailed above there are concerns about its robustness;
  • the recommended bed occupancy level is 85%, to allow for cleaning and operational factors
  • the figures below are yearly averages and do not reflect fluctuations in demand. Demand can be affected by seasonal variations, bed closures related to infection control and other operational factors. Levels of demand therefore fluctuate quickly, for example if a snapshot of recent data is taken, in June 2011 bed occupancy on Plemont medical ward was 82% (within the 85% recommended rate) but by July 2011 it had risen to 99%.

 

Average LOS

2005

2006

2007

2008

2009

Surgery

4.3

4.2

3.8

3.4

3.8

Medicine

7.9

7.8

7.6

6.1

8.1

Maternity*

-

-

-

-

-

 

Occupancy Rate

2005

2006

2007

2008

2009

Surgery

71%

68%

66%

N/A

72%

Medicine

90%

89%

89%

100%

80%

Maternity*

-

-

-

-

-

In the technical documents that support the Green Paper, KMPG clearly stated that JGH was running out of bed capacity. Through an analysis of 2010 occupancy rates, plus projections related to populated changes they concluded that:

  • an additional 20 medical beds would be required by 2015 to cope with activity and a further 40 beds would be needed to cope with the activity projected in 2040;
  • a similar rise was not required in surgical beds where peak demand in June and July was below the 85% occupancy (note: however that lack of available data meant KMPG was unable to assess demand created by medical patients placed in surgical beds because of lack of medical bed capacity).