In a recent INsite article, Max Robins, deputy chair of the New Zealand Aged Care Association (NZACA) and chief executive of CHT Healthcare Trust outlined the rationale behind the pay equity funding formula used to fund the residential aged care sector.

In this, Robins says it is difficult to see what alternative model could have been used. This is in response to questions over whether the funding could have been based on actual rather than averaged data. The home and community support services sector have based their model on actuals data.

“Unlike homecare, there is not a one to one relationship between resident numbers and staffing level, and occupancy and service mix change constantly,” states Robins in his article.

Linking the formula to these fluctuating occupancy levels has caused many providers concern.

In commenting on Robins’ article, aged care provider Louis Fick says it fails to address the effect of occupancy levels on the fee rate, which is “the most significant deficiency of the funding model”.

“Adjusting the funding model to the average or median occupancy level would have eliminated most of the issues as occupancy has the single biggest impact,” states Fick.

“Not many facilities would have a continuous 100 per cent occupancy, but staff to full occupancy as staffing levels are not that flexible.

“This would have been as simple adjustment not affected by staffing or education levels. Subsequent approval of qualifications, after the funding was put in place, is also not addressed.”

Fick questions whether Robins is supporting the Ministry of Health rather than the providers, or protecting the negotiations team.

However, Robins disputes this.

“I run a group with 16 facilities and have no desire to shoot myself in the foot by supporting the MOH at the expense of providers,” he told INsite. “My role was to represent providers in the best way I could using the information supplied by providers as the basis for calculating the impact of the settlement and putting forward the case on behalf of providers.”

Robins says ultimately the two factors that influence the cost impact are the number of hours of care per resident per day (HPRPD) and the wage differential.

“Occupancy has not been ignored as the hours per resident per day calculation includes the occupancy effect.

“When we surveyed providers we asked how many care hours they provided and how many residents they had on the survey day.

“This enabled us to calculate the hours per resident per day for each provider.”

Robins gives the following example to illustrate:

Provider One operates a 40-bed rest-home at 100% occupancy (i.e. 40 residents) while Provider Two operates a 40-bed rest-home at 75% (i.e. 30 residents). Both facilities run exactly the same roster.

Example roster:

Roster Total Hours
AM 4 x 7.5 Hours 30
AM 2 x 5 hours 10
PM 2 x 7.5 hours 15
PM 1 x 5 hours 5
Night 2 x 8 hours 16
Total care hours per day 76

Hours per resident per day – 40 residents = 1.90

Hours per resident per day – 30 residents = 2.53


Cost Impact 40 Residents 30 Residents
HPRPD 1.90 2.53
Average Rate Increase 3.94 3.94
On Costs 21.67% 21.67%
Total Increase in Rates 4.79 4.79
Total Cost Impact 9.11 12.14


Average impact                                                 10.63


By averaging the hour per resident per day we were also averaging the occupancy impact, explains Robins.

He acknowledges that smaller rest homes are likely to feel more acutely the effects of fluctuating occupancy levels.

“However, for small facilities, there is practically no room to adjust staffing hours and therefore any change in occupancy has a significant impact on the gap between revenue and cost,” says Robins.



  1. I could email the information below as the pasting does not keep the layout.

    1. On 25/5/2017 at the FMG stadium the question was put to the Pay Equity presenter on what occupancy % was used in the funding model. The response was that occupancy does not come into it and not relevant.
    2. My calculations below shows that it is 100% occupancy based. Any drop in occupancy results in a shortfall.
    3. If the model did include the national occupancy then it would only have impacted on a providers if the occupancy level dropped below the national average.
    4. Reducing care staffing levels is only possible at lever levels of occupancy. Vacancy does not only happen in one level of care but over all levels of care and this cannot always be mixed.
    5. Calculations:
    RH Dem
    Hours per day per resident
    – Caregiver 1.8 2.73
    – Dt 0.16 0.23
    Total 1.96 2.96

    Actual beds in facility 41 43
    Total hours per day 80.36 127.28

    Income increase Rate Beds Occupancy Income
    * Dementia 14.21 43 100% 223,026
    * Rest Home 9.41 41 100% 140,821

    Per resident per day Annual Average New Rate Difference On Cost Total Increase Increased staff cost
    Increase in care cost Beds Care hours hours Rate 30/6/2017 1/07/2017 21.70%
    * Dementia 43 2.96 46,457 16.60 20.54 3.94 0.86 4.80 222,995
    * Rest Home 41 1.96 29,331 16.60 20.54 3.94 0.86 4.80 140,791

    If occupancy drops to 87% being national average –
    * Income at 87% – 316,547
    Shortfall (47,239)

    * Income at 95% – 345,654
    Shortfall (18,131)
    The above shows that the fee increase was calculted at 100% occupancy.
    You might be able to reduce staff hours depending on employment agreements if the ocupancy drops to 87% but at 95% you could not. Also different levels of care cannot be mixed.
    Dementia care clients cannot be placed in rest home beds or rest home beds in dementia beds. Moving residents around for improved efficiency is also not residents care centred.


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