interRAI and qualityMichele McCreadie, General Manager, interRAI Services

Marg Milne, Team Leader South, interRAI Services

Jacqueline Joseph, Team Leader North, interRAI Services

Quality of data:The interRAI data quality projectMichele McCreadie, General Manager interRAI Services

Good data?

D

interRAI data quality projectTo evidence that high data quality is achieved and maintained to

increase confidence in interRAI data

4

Commissioned by interRAI NZ Governance Board

Began March 2018

Use the interRAI data warehouse to evidence the quality of the data

Implement a process for quality review and improvement

interRAI data collection process

Rigorous data collection process currently in place, including:

• Assessment instruments well tested

internationally

• Assessors are qualified health

professionals

• Ongoing quality reviews of completed

assessments

• Single national software platform –

consistent and standardised.

5

interRAI data quality measures

Trends in population characteristics

Trends in clinical characteristics

Trends in convergent validity

6

LTCF Trends in population characteristics

Year Female %

Married %

Under 65

%Over 85

%Dementia

%Heart failure

%

2015-16 66% 25% 4% 54% 18% 8%

2016-17 66% 24% 4% 54% 18% 8%

2017-18 65% 25% 4% 54% 18% 8%

7

LTCF Trends in clinical characteristics

YearCognitive

Performance Scale 3+ %

Depression Rating Scale 3+

%

Activities of Daily Living

Hierarchy 3+ %

2015-16 45% 20% 44%

2016-17 44% 21% 44%

2017-18 44% 21% 43%

LTCF Trends in convergent validity

YearADLH

and CPSPain

and DRSCHESS

and CPSPain

and CPS

2015-16 0.55 0.16 0.13 -0.14

2016-17 0.55 0.16 0.12 -0.15

2017-18 0.54 0.16 0.12 -0.15

9

Data quality issuesD

ata

valid

ity

•Invalid National Health Index number

Dat

a co

mp

lete

nes

s

•Missing height and weight information

10

Invalid National Health Index• Unique

identifier assigned to every person who uses health and disability support services in New Zealand

• Specific format: AAA0000

11

• Any NHI number that does not fit the correct format or that has an incorrectcheck digit is referred to as invalid

• 350 invalid NHIs ≈ 680 assessments discovered in interRAI data warehouse (error rate = 0.2%)

Invalid NHIs by assessment type over time

12

0

50

100

150

200

250

2015-16 2016-17 2017-18

Contact assessment Home Care assessment LTCF assessment

Missing height and weight information

Used to monitor:

• nutrition

• hydration status

• weight stability over time.

•Affects interRAI outcome measures:

• Undernutrition Clinical Assessment Protocol (CAP)

• Quality Indicator (QI) – prevalence of unexplained weight loss

•Not measured because of clinical rationale

13

Missing height and weight information

14

0 00

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0

% o

f as

sess

men

ts

#REF! #REF!

15

Conclusions

•Overall high quality

• Stable trends over time and convergent validity between outcome variables

• Important to continuously monitor and improve data quality

• Important to evidence data quality

interRAI Quality indicatorsMarg Milne, Team Leader South

Quality indicators

17

Show patterns in service delivery

Cover a large number of aspects of service delivery

Are derived from the data in interRAI assessments

Uses of interRAI Quality Indicators

18

Better understand service quality

Identify areas where you are

doing well

Identify opportunities to improve quality

Track quality of care over time

Evaluate the impact of service

improvement exercises

Evaluate the influence on policy

decisions

Reports

19

National reports and education materials at

www.interrai.co.nz/data-and-reporting/quality-indicators

Facility reportsAll facilities may expect an individualised Quality

Indicator report in October

We will contact you by email when this is available

The report is available through Connex

DHBs will not have access to your individual Quality Indicator reports

20

Report charts

Each report contains five charts, One for each level of care

All levels of care

Resthome Hospital DementiaPsycho-geriatric

21

Example

22

interRAI Quality Indicators• National• April to June 2018• Care level group: Resthome Care

X National (previous quarter)X National (current quarter)

Example

• Yellow triangle = my facilities current quarter’s score

• White triangle = my facility’s previous quarter’s score

• Green cross = the national average score

23

24

Understanding prevalence and incidence

Not all quality indicators will or should change in the same direction over time.

PrevalenceWe want to see:

A lower pattern of scores over time

Declined incidenceWe want to see:

A lower pattern of scores over time

Improved incidenceWe want to see:

A higher pattern of scores over time

Responding to reports• Quality indicators are developed in

ways to balance the findings

• No individual facility will be good or poor at everything

25

For example:Resident falls are reported at the same time as the facility’s use of restraints

Suggestions for responding to the report

Evaluate your performance compared to the reported

average and previous quarter

• Are trends in the right direction?

• Any investigation required for underlying factors that may have led to the results?

• Do others involved in care feel the report is consistent with their experience?

Use the results to inform your quality plan

• Is there an area/s to prioritise in your quality efforts?

• Do you need to develop strategies to changeyour practice patterns in the facility?

• Are their any targets to set for your performance improvement?

• Share with the care team the indicators that signal that you are excelling.

26

27

FuturePeriod of ‘surveillance’:

• Users will understand indicators.

• Providers will use this information to reflect on the care they provide.

• Positive New Zealand examples of care will be promoted.

• Positive news and case studies of quality care will be shared.

Over time (2019):

• Shift to risk adjustment system.

• Individuals with similar clinical features are compared.

Quality of life:interRAI Wellbeing measuresJacqueline Joseph, Team Leader North

‘older people live well, age well, and have a respectful end of life in age-friendly communities’

29

Healthy Ageing Strategy 2016

Key wellbeing measures

30

Physical and mental health status

Independence

Safety

Positive relationships

Responsibilities and directives

Health status – most commonly diagnosed disease

31

19%

23%

25%

26%

37%

0 5 10 15 20 25 30 35 40

Diabetes mellitus

Stroke/CVA

Depression

Coronary heart disease

Dementia other than Alzheimers

Long Term Care Facilities in %

Mental health – DepressionDepression clinical diagnosis vs. Depression Rating Scale (DRS) by ethnicity

32

17%

22%

15%

10%

20%18% 21% 18%

14%

21%

0%

5%

10%

15%

20%

25%

Asian European Maori Pacific Peoples Other Ethnicity

% with Depression clinical diagnosis % Depression Rating Scale 3+

Independence – Activities of Daily Living (ADL) >3

33

European Māori Pacific Peoples Asian Other Ethnicity

Level 3

Level 4

Level 5

Level 6

34

Safety – Falls risk

<65 65-74 75-84 85+

Positive relationships – Social relationship CAP

35

No

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Responsibilities and directives – EPOA

36

No

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EPOA by care level

37

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Dementia Hospital care Other care Psycho-geriatriccare

Respite care Resthome care

No

Yes

www.interrai.co.nz