Danish Fracture Database DFDB.DK

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1 Danish Fracture Database DFDB.DK Herlev Sygehus Kirill Gromov, MD, PhD, - [email protected]

2 Purpose of DFDB Web-based prospective quality monitoring of fracture related surgery Evaluation: Rates of reoperation Operative parameters 2

$fracture related surgery$

3 Assessment of Quality Why assessment of quality is relevant: Life time prevalence of getting a fracture is 38.2 % 20,000 fracture related surgeries are estimated to be carried out annually in DK No prospective data for assessing the quality of fracture related surgery in general has previously been collected 3

$2 % 20,000 fracture related surgeries are estimated to be carried out$

4 Need for registry based research Observational data Treatment guidelines Implant monitoring

5 History of DFDB 6 years ago: Paper and pen-based database tested at Aabenraa Hospital 2 years ago: Web-based database initiated at Hvidovre and Odense Hospitals, Dept. of Orthopaedics Now: 21 departments in total Administration and statistics» Steering group with annual meetings Michael Brix Anders Troelsen 5

6 Participating departments Hvidovre Odense Rigshospitalet Slagelse Køge Nykøbing F. Hillerød Århus Vejle Gentofte Kolding Aabenraa Herlev Bispebjerg Esbjerg Holbæk Viborg Horsens Aalborg & Farsø Randers 21 departments n 35,000 operations 6

Hillerød Århus Vejle Gentofte Kolding Aabenraa Herlev

7 Completeness and validity Early data completeness and validity COMPLETENESS Hvidovre Odense Both Departments Primary surgeries 90% (145/161) 86%(102/118) 88% (247/279) Reoperations 84% (27/32) 71% (22/31) 77% (49/63) DATA VALIDITY App % Gromov et al., DMJ, oktober

(145/161) 86%(102/118) 88% (247/279) Reoperations 84% (27/32) 71%

8 DFDB History of data entries > 8000 entries / 6 months 8

9 Structure DFDB.dk online registration, developed by PROCORDO 2 min per registration Filled out by the surgeon immediately after surgery Patient, trauma and surgery related factors are registered Reoperations are linked with primary operations 9

10 Data Departments own their own data Department can use data for quality monitoring, research etc. Departments can veto use of data in projects by other departments Departments deliver data for annual report at the DOS congress All rules followed, all is reported to The Danish Data Protection Agency Alle departments have a person responsible for data who is also member of the steering group 10

annual report at the DOS congress All rules followed, all is reported to The Danish Data

11 User featers Status messages Surgical log

12 Kirill Gromov, læge, PhD, - [email protected] Status messages

13 Fremtid Landsdækkende database (ansøgning til SSI indsendt) Flere forskningsprojekter Implantat sporing 13

14 Forskningsprojekter 4 artikler i Pubmed 1 accepteret til JBJS surgical delay. Danish Fracture Database Collaboration ordning. Flere på vej???

15 Surgical Delay 3517 primary surgeries for low energy, non-pathological AO31A and AO31B fractures on patients age > 50 were identified from DFDB. Median age: 82.0 (range ) AO31A (trochanteric) 1729 (49%) Female 2458 (70%) Primary Endpoint : 30-day and 90-day mortality (Civil Registrational system). Modifiable Risk Factors: Surgical delay = From diagnostics (x-ray) to onset of surgery. Educational level of surgeon AA = Attending or above BA = Below attending Nyholm et al. JBJS. Accepted 15

0 (range 51-107) AO31A (trochanteric) 1729 (49%) Female 2458 (70%) Primary Endpoint : 30-day and 90-day mortality (Civil

16 Surgical Delay Mortality Surgical delay 16

17 Logistical regression* *Adjusted for age, gender, ASA score, fracture type, treatment, educationale level of surgeon/surgical delay Surgical delay 30-day mortality risk (OR) 90-day mortalit y risk (OR) 12 vs <12h 1.45* vs <24h 1.34* 1.23* 36 vs <36h * 48 vs <48h 1.56* vs <72h Surgical delay 30-day mortality risk (OR) 90-day mortalit y risk (OR) <12 h h h 1.60* h h 2.61* 1.83* 72 h Educatilnal level of surgeon 30-day mortality risk (OR) 90-day mortality risk (OR) AA 1 1 BA 1.28* 1.26*

36 72 vs <72h 1.23 1.09 Surgical delay 30-day mortality risk (OR) 90-day mortalit y risk (OR) <12 h 1 1 12-24 h 1.33 1.02 24-36 h 1.60* 1.

18 Conclusions Short surgical delay (<12h) reduces risk of 30-day mortality. The effect is less pronounced at 90-day mortality. Junior surgeons should be supervised.

19 IMPLANTATSPORING Hvidovre Hospital Intelligent implantat sporing & klassifikation Kirill Gromov, læge, PhD, - [email protected] 19

20 Implantat sporing Behov Det anvendte implantat skal kunne identificeres entydigt og specifikt ved angivelse af implantatets navn og model, størrelse af implantatet, fabrikantens navn, serienummer eller LOT efterfulgt af batchkode 1) Hvad har vi opereret patienten med? Reoperationer Recalls 2) Hvordan går det med det nye implantat? Kontinuerlig kvalitets monitorering Kirill Gromov, læge, PhD, - [email protected] 20

LOT efterfulgt af batchkode 1) Hvad har vi opereret patienten med?

21 Implantat sporing idag 1) Hvad har vi opereret patienten med? Reoperationer Recalls Kirill Gromov, læge, PhD, - [email protected] 21

22 Implantat sporing idag 2) Hvordan går det med det nye implantat? Kontinuerlig kvalitets monitorering Kirill Gromov, læge, PhD, - [email protected] 22

23 Implantat sporing i fremtiden Nem tilgængelig og med landsdækkende potentiale Løbende monitorering med early warnings Intelligent implantat sporing med klassifikation Kirill Gromov, læge, PhD, - [email protected] 23

24 Hvorfor klassificere? Er det ikke nok at kende firmaet og lot nummeret nummeret? Kirill Gromov, læge, PhD, - [email protected] 24

25 1978 Ford Pinto Barbecue that seats four Kirill Gromov, læge, PhD, - [email protected] 25

26 Defekt produktion, design eller noget helt tredje? Kirill Gromov, læge, PhD, - [email protected] 26

28 Defekt produktion, design eller noget helt tredje? Kirill Gromov, læge, PhD, - [email protected] 28

29 Indføring af cladestik Kirill Gromov, læge, PhD, - [email protected] 29

30 Implantatklassifikation giver større viden Sammenligning på tværs af producenter Mulighed for at kigge på flere faktorer samtidigt Identificering af fejl i designet Mulige farlige kombinationer Kirill Gromov, læge, PhD, - [email protected] 30

31 Cladestik ved implantatregistrering Klassificeres første gang af kirurgen En implantat skal kun klassificeres en gang Alle implantater klassificeres Valideres af superbruger Kirill Gromov, læge, PhD, - [email protected] 31

32 Overlevelses kurver 32

33 Overlevelses kurver 33

34 Aktuel status på Marvsøm Hvad er evidensen for brug af forskellige implantater til proximal femur frakturer?

35 Begrænsninger: Engelsksproget publiceret 1990 eller senere. Trochantær eller collum fem (dvs. ikke pipkin eller distalt for troc. minor) Primære hoftefracture Ikke patologisk Angive failure of implant Min.follow-up 1 år Klart angive implantat

36 Søm Implant N (studies) N (patients) Prospective N (patients) Retrospective N (patients) total Gamma IMHS InterTan PFN PFNA PTN

37 HUSK AT REGISTRERE I DFDB

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