Avoidable utilization of hospital care among elderly patients with significant health care needs...

Avoidable utilization of hospital care among elderly patients with

significant health care needs

Limitations in the use of process and outcome measures to incentivize quality improvements in

primary care .

Anders Anell & Anna H Glenngård

Lund University / School of Economics and Management

Mean number of bed-days per person 75+ registered across different primary care practices in Region Skåne, Sweden, year 2011.Inclusion criteria = 1,7% with highest ACG-weight, aged 75+


Possible indicators for pay-for-performance (P4P)• Outcome indicators

– Visits to hospital emergency units without admission per 1000 registered

– Utilization of in-patient care, re-admissions within 30 days

• Process indicators– Continuity– Drug reviews– Individual patient plans (in collab. with community

staff)Outcome is explained by:

- evidence of interventions- quality of implementation- riskfactors och patient attributes- randomnes

process Type I (false positive) and type II (false negative) error when assessing practices


Data and Metod

• Qualitative study – step 1– Blinded interviews with eight practices and

community staff– Assessment of case finding, continuity, access,

coordination and collaboration between primary and community care

– Summarizing index compared with hospital utilization and socioeconomic status of registered individuals

• Quantitative study – step 2– Data from 150 practices in regression analysis – Dependent variables: Mean beddays per person 75+;

Visits at emergency care units without admission per 1000 registered 75+

– Independent variables: location, CNI (socioeconomic status), private or public, continuity, drug reviews, individual patient plans, direct admissions


Name of providers (anonymous)

Case-finding

Continuity towards patient

Accessibility towards patient

Collaboration between primary and community care

Coordination of care based on individual needs Sum

Author assessment (interview data)


Continuity in three consecutive visits (registered data)


Author assessment of formal structure (interview data)

Author assessment of accessibility and continuity (interview data)

Self-rated by primary care

Self-rated by community care

Number of individual patient plans (registered data)

Number of drug reviews (registered data)

Tärnan *** *** * *** *** *** *** * - ** 22

Doppingen ** *** ** ** * *** * * - - 15

Måsen ** *** ** *** *** *** ** * - - 19

Svalan ** ** * * * ** ** * - ** 14

Lommen ** ** * * ** ** ** * * *** 17

Vadaren * ** ** ** ** *** ** * - *** 18

Svanen *** *** ** *** *** *** *** ** ** *** 27

Falken ** ** * ** *** *** ** ** - * 18

Assessment of case finding, continuity, access, coordination and collaboration between primary and community care


Name of provider (anonymous) and summary points from table 1

Average number of bed-days per elderly patient with high ACG, years 2011 and 2012

Number of visits at emergency units without admission per 1 000 individuals > 75 years, Jan-Sept 2012

Level of socioeconomic deprivation of registered individuals

Svanen, 27 points 5 resp. 6 150 Low

Tärnan, 22 points 10 resp. 8 200 Average

Måsen, 19 points 7 resp. 8 150 Average

Doppingen, 15

points

5 resp. 4 250 Low

Svalan, 14 points 9 resp. 5 400 Average

Lommen, 17 points 7 resp. 6 350 Average

Falken, 18 points 11 resp. 8 400 High level

Vadaren, 18 points 11 resp. 9 400 High level

Comparison between summary index, outcome indicators and socioeconomic deprivation (CNI).


Reflections

• Insufficient routines to handle elderly in ordinary housing

• Lack of coordination based on individual needs

• Gap between formal responsibility and practical work

• Insufficient information flow between different care givers

• Continuity compensate for poor coordination and cooperation


Results from regression analysis

• Two models– mean number of bed-days and visits at

emergency units without admission per 1000

• Significant correlation with location of practices in both models– Increased CNI results in increased mean

number of bed-days and number of visits– Lower number of visits in two out of five

districts• Higher percent of direct admissions reduces

mean number of bed-days• The model with bed-days as dependent

variable explains less of variance


Explanatory model with “visits to emergency unit without admission per 1000 individuals > 75 years” as the dependent variable.

VariableBeta (standardized) Sig (p-value)

Constant 12,487 ,000

District: Mid=1, Other=0 -8,668 ,000

District: North East=1, Other=0 -3,742 ,000

Socioeconomic status (measured by CNI)

3,186 ,002

Adjusted R2 0,425

Observations (number of providers) 145


Explanatory model with “average number of bed-days per person” as the dependent variable.

VariableBeta (standardized) Sig (p-value)

Constant 7,372 ,000

Socioeconomic status (measures by

CNI)4,398 ,000

Direct admission (proportion of direct

admissions to hospital wards without

passing the hospital emergency units)-2,660 ,009

Adjusted R2 0,171

Observations (number of providers 144


Limitations of indicators• Wrong practices may be rewarded when using

outcome meausers– Need to adjust for patient attributes (e.g. CNI)– Limitations when number of patients are limited

(randomness)– Several factors may influence outcomes

(attribution problem)• But process indicators have important

limitations as well– Evidence base?– Often easy to manipulate– ”Box ticking”, ”treat-to-test”, ”reaching target

but missing the point” – Need to secure quality in implementation

Avoidable utilization of hospital care among elderly patients with significant health care needs...

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