W O R D C L O U D O F M Y T H E S I S
K A T H R I N D E N T L E R V R I J E U N I V E R S I T E I T A M S T E R D A M & A C A D E M I S C H M E D I S C H C E N T R U M U N I V E R S I T E I T VA N A M S T E R D A M
W H I C H H O S P I TA L S H O U L D H E C H O O S E ?
D O T H E S E P H Y S I C I A N S M E E T T H E H I G H E S T S TA N D A R D ?
Q U A L I T Y I N D I C AT O R S
• Voluntary and legally mandatory
• Structure, process and outcome
• Based on evidence or consensus
S A M P L E I N D I C AT O R ( R E P O R T I N G Y E A R : 2 0 1 3 )
% (numerator / denominator) e.g. 85% (39 / 46)
Numerator: Number of patients who had 10 or more lymph nodes examined after resection of a primary colonic carcinoma.
Denominator: Number of patients who had a resection of a primary colonic carcinoma.
Exclusion criteria: e.g. previous radiotherapy
P R O B L E M S
• Increasing number of indicators; manually calculated => increasing workload and costs
• Varying interpretations of ambiguous natural language => doubtful results
“ U N D E R W H I C H C O N D I T I O N S C A N H E A LT H C A R E Q U A L I T Y I N D I C AT O R S B E C O M P U T E D A U T O M AT I C A L LY ? ”
Computing Healthcare Quality
Indicators Automatically
Secondary Use of Patient Data
and Semantic Interoperability
Kathrin Dentler
Computing H
ealthcare Quality Indicators Autom
atically
Kathrin Dentler
K A T H R I N D E N T L E R
I)
II)III)
F O R M A L I S AT I O N M E T H O D C L I F
Numerator: Number of patients who had 10 or more lymph nodes examined after resection of a primary colonic carcinoma.
Exclusion criterion: previous radiotherapy
‣ CLIF’s Reproducibility: 8 students formalised same indicator
‣ CLIF’s Generalisability: formalised 159 indicators and computed them based on data from the Julius General Practitioners’ Network Database
F O R M A L I S AT I O N M E T H O D C L I FPA R T I ) C O M P U T I N G H E A LT H C A R E Q U A L I T Y I N D I C A T O R S A U T O M A T I C A L LY
S E C O N D A R Y U S E O F PAT I E N T D ATAPA R T I I )
G I O C A : G A S T R O - I N T E S T I N A L O N C O L O G Y C E N T R E A M S T E R D A M
PA R T I I ) S E C O N D A R Y U S E O F PA T I E N T D A TA
‣ Barriers to the secondary use of patient data
‣ Influence of data quality on indicator results, e.g. indicator results based on
- primary data (external registry): 88% (36/41)
- secondary data (hospital): 58% (31/53)
S E C O N D A R Y U S E O F PAT I E N T D ATAPA R T I I )
E S S E N T I A L I N H E A LT H C A R E PA R T I I I ) S E M A N T I C I N T E R O P E R A B I L I T Y
‣ Product test for reasoning engines
‣ Analysed redundant elements in SNOMED CT
S E M A N T I C I N T E R O P E R A B I L I T YPA R T I I I )
• Automated computation of indicators is feasible, but
✓ Indicators need to be formalised
✓ Data needs to be of adequate quality, and
✓ Semantic interoperability is required
C O N C L U S I O N S