Mean number of bed-days per person 75+ registered across different primary care practices in Region Skåne , Sweden, ye

1. 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

2. 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+

3. 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 • riskfactorsoch patient attributes • randomnes TypeI (false positive) and typeII (false negative) errorwhenassessing practices process

4. Data and Metod • Qualitativestudy – step 1 • Blindedinterviews with eightpractices and communitystaff • 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 practicesin regression analysis • Dependent variables: Meanbeddays per person 75+; Visits at emergencycareunitswithoutadmissionper 1000 registered75+ • Independent variables: location, CNI (socioeconomic status), private or public, continuity, drugreviews, individual patient plans, directadmissions

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

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

7. 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

8. 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

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

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

11. Limitations ofindicators • Wrongpracticesmay be rewardedwhenusingoutcomemeausers • Need to adjust for patient attributes (e.g. CNI) • Limitationswhen number of patients are limited (randomness) • Several factors may influence outcomes (attribution problem) • But process indicatorshaveimportant limitations as well • Evidencebase? • Often easy to manipulate • ”Box ticking”, ”treat-to-test”, ”reaching targetbutmissing the point” • Need to secure quality in implementation