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Table 2 Project outcomes and outcome measures in the PATINA study

From: Prevention of AcuTe admIssioN algorithm (PATINA): study protocol of a stepped wedge randomized controlled trial

 

Outcome

Outcome measure

Primary outcome

Outcome 1

Acute admission

Proportion of acute hospital admissions after being identified at risk by the algorithm

Secondary outcomes

 Outcome 2

Preventable admission

Preventable admission after being identified at risk by the algorithm

 Outcome 3

Readmission (30-days)

Readmission to a Danish hospital within 30 days from a hospital discharge

 Outcome 4

Outpatient contacts

Proportion of contacts to outpatient clinics after being identified at risk by the algorithm

 Outcome 5

Primary care physicians contacted

Contacts to a primary care physician after being identified at risk by the algorithm

 Outcome 6

Death (90-days)

Proportion of diseased citizens identified at risk by the algorithm within 90 days

Health care utilization and economic outcomes

 Outcome 7

Changes in utilization and costs of municipal home, nursing and social care services

Information on municipal home, nursing and social care services will be collected as part of the data used in the PATINA algorithm. Costs will be summed from the first date a citizen is identified at risk by the algorithm

 Outcome 8

Changes in utilization and costs of planned and unplanned hospital treatment

Information on hospital treatment (planned and unplanned) will be collected from the Danish National Patient Registry. Costs will be summed from the first date a citizen is identified at risk by the algorithm

 Outcome 9

Changes in utilization and costs of contacts to primary care physicians

Information on contacts to primary care physicians will be collected from the Danish National Health Insurance Service Register. Costs will be summed from the first date a citizen is identified at risk by the algorithm

 Outcome 10

Cost of implementation of the PATINA algorithm and decision support tool

The cost of implementing the algorithm and decision support tool will be calculated as time total time spent for introduction and working with the algorithm for each nurse

Process outcomes

 Outcome 11

Barriers and facilitators for nurse’s acceptance and use of the algorithm

Data will be collected as a three-wave survey, which will be integrated in SW-CRT design and follow the step-wise implementation of the algorithm in each of the tree municipalities