Alain Guignandon
email: alain.guignandon@univ-st-etienne.fr

Nadia Boutahar

Aline Rattner

Laurence Vico

Marie-Hélène Lafage-Proust

Cyclic strain promotes shuttling of PYK2/Hic-5 complex

Keywords: PYK2, FAK, Hic-5, Paxillin, focal contact, osteoblasts, cyclic strain PYK2/Hic-5 and PYK2/FAK association under cyclic strain

teaching and research institutions in France or abroad, or from public or private research centers.

INTRODUCTION

It is now well evidenced that mechanical strain plays a major role in the maintenance of bone mass. Osteoblasts, the bone forming cells appear to be the key effectors of osteogenic mechanical stimuli and in vivo studies suggested that loading-induced increase in bone formation was related to an increase in osteoblast recruitment ( 1 ). However, the molecular mechanisms that mediate this response are not clearly identified. Several lines of evidence suggested that integrins, which represent a convergence point of several signals and transmit tension to extracellular matrix (ECM) and to the intracellular structures, including the nucleus, are essential for the signal transduction of a mechanical stimulus ( 2 ). In a previous study, we showed that cyclic stretching of osteoblasts induced an increase in size and number of adhesion plaques, immuno-stained with phosphotyrosine antibodies, demonstrating the involvement of integrins in osteoblastic mechanotransduction ( 3 ). Futhermore, we showed that the strain-induced mitogenic response of osteoblast-like cells depended upon ERK activation under the control of FAK and PYK2 ( 4 ), two yrosine kinases which colocalize to the adhesion plaques ( 5 ). FAK and PYK2 are closely related in their overall structure with about 46% sequence identity (65% similarity) over their entire length ( 6 ). They are both phosphorylated by integrin binding ( 7 , 8 , 9 ); however, PYK2 can also be activated by intracellular calcium changes. Interestingly, it was recently shown in F9 cells that adhesiondependent activation of ERK is mediated by FAK-paxillin binding ( 10 ). Paxillin is an adaptor molecule of 559 amino-acids which contains numerous potential protein-protein binding sites, including proline-rich regions, SH2 binding sites and four LIM domains ( 11 , 12 , 13 ). Beside FAK, paxillin interacts with several other protein such as Src family-SH3 domains ( 14 ) and vinculin ( 15 ). Hic-5, a protein with high homology with paxillin was shown to share some of its binding partners such as FAK, PYK2, Csk, vinculin, and PTP-PEST ( 16 ). Hic-5 can be phosphorylated on tyrosine residues, although the sites of tyrosine phosphorylation in paxillin are not conserved in Hic-5 ( 17 ). Interestingly, unlike their respective homologues paxillin and FAK, both Hic-5 and PYK2 are not exclusively found at the adhesion plaque. Indeed, Hic-5, which bears a NES sequence, was reported to shuttle to the nucleus under various stimuli ( 18 ), while PYK2 was observed into both the nucleus and the cytoplasm. It has been reported recently in smooth muscle cells, that HIC-5 is sequestered by actin-stress fibers under mechanical strain ( 19 ). These differential subcellular localisations suggested that these focal adhesion proteins might play a role in mechanotranduction (19) and transcription of target genes ( 20 ). In this context, our aim was to further analyse the kinetics of activation and subcellular localisation of PYK2 and HIC-5 in osteoblast-like cells submitted to mitogenic mechanical strain.

MATERIALS and METHODES

Materials

Horseradish peroxidase-conjugated goat anti-rabbit (P0448) and Horseradish peroxidaseconjugated horse anti-mouse (P0447) antibodies were obtained from DAKO. Anti-Ptyr (PY99) and anti-FAK (H-1) antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, CA).The anti-PYK2 mouse monoclonal antibody was obtained from Transduction Laboratories (Montluçon, France). The anti-paxillin mouse monoclonal was obtained from Upstate Biotechnology (Mundolsheim, France) and the anti-Hic-5 mouse monoclonal clone 34 was obtained from BD Biosciences Pharmingen (Le Pont-De-Claix, France). ECL detection reagents were purchased from Pierce (Montluçon, France). Stripping solution Re-Blot Plus was obtained from Chemicon International (Temecula, CA)

Cell culture

We used ROS 17/2.8 osteoblast-like cells, a well-defined cell line ( 21 ) with the characteristics of mature osteoblasts (alkaline phosphatase activity, osteocalcin and type I collagen expression, and ability to mineralize), and the MC3T3-E1 mouse osteoblastic cell line. Cells were grown in humidified atmosphere with 5% CO 2 at 37°C. ROS 17/2.8 cells were cultured in DMEM, and MC3T3-E1 cells in α-MEM, both supplemented with 10% FCS, 2mM Lglutamine, 100 U/ml penicillin and 0.1mg/ml streptomycin. After reaching a subconfluent state, cells were trypsinized with 1X trypsin-EDTA, counted and plated.

Cyclic deformation

The Flexcell Strain Unit Fx-3000 (Flexcell Corp, McKeesport, PA) was used for application of mechanical stretch to osteoblasts ( 22 ). Cells were plated in six well tissue culture dishes with type I collagen-coated flexible silicone bottoms at 1.10 4 cells per cm 2 density for seventy two hours after seeding, cells were serum-starved overnight and then subjected to mechanical deformation. Mechanical deformation was induced with a Flexercell Strain Unit (Bioflex, Flexcell Corp, McKeesport, PA), which consists in a vacuum manifold regulated by solenoid valves that are controlled by a computer timer program. Six buttons insert into each plate, each allowing a uniform magnitude of the strain across 85% of the surface of a flexible well.

For these experiments, an 80 kilopascals negative pressure was applied to each culture plate, through an air pump, bottoms were deformed to a known percentage of elongation and then releasing the membranes to their original shape. The experimental regimens used in this study delivered 1% elongation and at a rate of 15 cycles/min (2s deformation period followed by a 2s neutral position). Cells remained adherent, and the deformation of the membrane is directly transmitted to cells. Cells grown on unstretched Bioflex plates were used as controls.

Immunoprecipitation

Cells were lysed in buffer (25 mM tris PH 7.5, 150mM NaCl, 1% IGEPAL, 1% sodium deoxycholate, 0.1% SDS, 50mM sodium fluoride, 10Mm Sodium Pyrophosphate, 1mM AEBSF, 0.1 Unit/ml aprotinin, 10µg/ml leupeptin, 1mM Sodium orthovanadate). Lysates were clarified by centrifugation at 14,000 rpm for 30min. Supernatant were transferred to fresh tubes. Protein concentration of lysates was determined with the bicinchoninic acid assay (Pierce, Rockford, IL).

Immunoprecipitations were typically performed with 1-2mg of cell lysate and 2µg of purified monoclonal or polyclonal antibody. After incubation at 4°C for 2h on rotating device, immune complexes were precipitated at 4°C overnight on rotating device by using protein A sepharose (Sigma, St-Quentin Fallavier, France). Immunoprecipitates were washed three times with lysis buffer and extracted in 2X SDS-PAGE sample buffer (125mM Tris-HCl,pH 6.8, 4% SDS, 20% glycerol, 10% β-mercaptoethanol, 0.025% bromophenol blue) by 5min boiling and electrophoresed by SDS-PAGE and analysed by western blotting.

Western blot analysis

After SDS-PAGE, proteins were transferred to nitrocellulose membrane (Bio-Rad,Hercules,CA). After transfer, membranes were blocked with 5% non-fat dried milk in PBS, pH 7.4, and incubated overnight at 4°C with the anti-p-Tyr (PY99) , anti-FAK, anti-PYK2, anti-Paxillin ,or anti-Hic-5 antibodies, 0.1 µg/ml. Membranes were washed three times with TBS (0.1% Tween 20) and then incubated with secondary antibodies (peroxidaseconjugated goat anti-rabbit,1:2000 or horse anti-mouse,1:6000) for 1h at room temperature.

After washing three times with TBS, 0.1% Tween 20, the immunoreactive bands were visualized using ECL detection reagents. Immunoblot were stripped with mild antibody stripping solution and reprobed. Levels of tyrosine phosphorylation and the amounts of protein were quantified using a software Scion Image program for densitometry analysis (Scion Corporation, suite H, Maryland). Each band was normalized to the total protein level in the respective sample. Immunoblots shown in this paper are representative of at least two separate experiments.

Immunostaining was performed on stretched and control cells at various time points after the end of the stimulation. Cells were fixed in 4% paraformaldehyde for 10 min, washed with cold PBS and permeabilized with 0.1% triton X-100 in PBS for 2 min. Anti-FAK, anti-PYK2, anti-Paxillin, or anti-Hic-5 antibodies (1:100 in PBS/BSA 1%) were applied for 1H at 37°C and cells were rewashed in PBS on a rocking platform. Cells were incubated with fluorescein isothiocyanate (FITC)-conjugated goat anti-mouse or anti-rabbit IgG (1:100 in PBS/BSA 1%) for 1h at 37°C. Immunostaining was observed with fluorescence microscope (Leica DMRB, Lyon, France) and acquired with a cooled CCD camera (CoolSNAP.fx, Roper Scientific, Evry, France) with Metaview system software (Universal Imaging Corp, Downingtown, PA, USA).

RESULTS

Tyrosine phosphorylation of pp125 FAK , PYK2, Paxillin and HIC-5 induced by mitogenic cyclic strain.

Tyrosine phosphorylation of cellular proteins was examined by immuno-blotting using antiphosphotyrosine monoclonal antibody. In response to cyclic strain, a time-dependent tyrosine phosphorylation of several proteins was observed in rat osteosarcoma cell line (ROS 17/2.8) cells (Fig 1A ) as well as in the mouse osteoblastic cell line MC3T3-E1 (data not shown). We found 2 clusters of proteins detected at 110 -125 kDa and at 50 and 65 kDa that might correspond to FAK/PYK2 and paxillin/Hic-5, respectively. The increase in tyrosine phosphorylation level was detected as early as the end of strain and was extended up to 4h for both clusters. In order to identify more precisely the phosphorylation time course of the four focal contact proteins, we first performed an immunoprecipitation of pp125 FAK

Distinct localisations of focal contact proteins induced by cyclic strain.

As the time course of phosphorylation of the four focal contact proteins was roughly similar, we focalized on the relocalisation and physical interactions of these proteins under cyclic strain. The homologous proteins paxillin and Hic-5 exhibited different subcellular localisations induced by mechanical strain. Paxillin immunofluorescence staining essentially localized to focal adhesion plaques and remained unchanged in strained compared to control cells (Fig 2A). In contrast, Hic-5 immunostaining showed a significant fraction of Hic-5 protein shuttling from the focal contact to the cytoplasm 30 min. after strain and appeared associated with fibrillar structures of the cytoskeleton after 240 min (Fig. 2C). FAK remained at the focal contact regardless of the time point observed (Fig. 2B). In contrast, PYK2 shuttled from focal contact to perinuclear regions of the cytoplasm 30 min after strain, this diffuse cytoplasmic localization observed under basal conditions was resumed 240 min after strain (Fig. 2D). In order to illustrate more precisely the Hic-5 localisation after cyclic strain, we visualised Hic-5 in the nuclear plane 30' after strain (Fig. 3A) and found that Hic-5 was not present is the nucleus, moreover in the same field, punctuated staining were detected in apical structures of the cells (Fig. 3B) demonstrating that central staining observed in Fig. 2B &2C could not be attributed to a nuclear translocation of Hic-5 under strain. Using a larger magnification, we demonstrated that Hic-5 was clearly associated with fibrilllar structures 240' after strain (white arrows) (Fig. 3C).

Interactions between focal contact proteins are modified by cyclic strain.

In the present study, co-immunoprecipitation experiments evidenced a strong and constant interaction between Paxillin and PYK2 regardless of the mechanical condition (Fig. 4A).

Association between PYK2 and Hic-5 increased in a time-dependent manner under strain (Fig 3C) as well as the association of PYK2 and FAK (Fig. 4D). These associations were specifically induced by cyclic strain because as demonstrated by the absence of complexes in unstrained cells. Conversely, the association between Hic-5 and paxillin decreased during the 240 minutes of recovery after strain (Fig 4B). These results suggest that paxillin and FAK which are both phosphorylated under mechanical stimulus remained localized to the focal contact. In contrast, a fraction of PYK2 and Hic-5 shuttled out of focal contact inducing a release of Hic-5 from paxillin. Interestingly, in the same time, we observed a strengthening of PYK2/FAK association under mechanical strain (Fig. 4D) suggesting a central role of PYK2 in osteoblasts submitted to cyclic strain.

DISCUSSION

We previously showed that tyrosine kinases FAK and PYK2 are critical for strain-induced increase in osteoblastic proliferation (3). However, knowing the complexity of the relationships between their signalling partners, further analyses were needed to begin to decipher their respective role in osteoblastic mechanotransduction pathways. In endothelial cells exposed to hemodynamic shear stresses, the spatial reorganization of focal adhesion proteins associated with mechanotransduction plays a major role, especially because the forces vary greatly over subcellular distances ( 23 ). Thus, we investigated spatiotemporal components of signalling molecules such as FAK, Paxillin and their homologues PYK2 and Hic-5 in osteoblasts.

In the present study, beside FAK and PYK2, we found that paxillin and its homologue Hic-5 were also tyrosine-phosphorylated under mechanical strain. These four proteins localised to focal contacts under basal conditions and cyclic strain led to a shuttling of a Hic-5/PYK2 complex out of the focal contacts while FAK and paxillin remained to the focal contacts throughout the time points considered. Interestingly, the Hic-5/paxillin association decreased under mechanical strain. This suggested that, in unstrained cells, paxillin sequestered Hic-5 at the focal adhesion sites and that mechanical strain led to a release of Hic-5 from paxillin. Hic-5 and paxillin share many similar binding partners, but it was shown that Hic-5 antagonizes paxillin functions. For instance, the LD3 motif of Hic-5, which corresponds to the paxillin LD4 motif, is required for Hic-5 mediated inhibition of cell spreading, possibly by sequestering FAK from paxillin ( 24 ). Once associated with cytoskeletal structure such as actin stress fiber as clearly demonstrated by Kim-Kaneyama et al. (19), Hic-5 down regulates factin contractility by its association with GIT1 an Arf GTPase activating protein ( 25 ) known to switch from cytoplasmic location to f-actin fibers ( 26 ). As stress fibers polymerization is a common biological response to mechanical stimulation ( 27), it can be speculated that shuttling of Hic-5 from focal adhesion to cytoskeleton increases f-actin turnover.

It is also known that Hic-5 can transfer from focal adhesions to the nucleus in response to H 2 O 2 in MC3T3 osteoblast-like cells ( 28). Once localized in the nucleus, Hic-5 was involved of in endogenous c-fos induction by H 2 O 2 in osteoblasts and stromal cells lines [START_REF] Shibanuma | Hic-5 communicates between focal adhesions and the nucleus through oxidant-sensitive nuclear export signal[END_REF]. Finally, Hic-5 was reported to bind to steroid receptors and act as a transcription coactivator in transient reporter assays ( 29 , 30 ). As we demonstrated that Hic-5 is never localized within the nucleus (Fig. 4A) after cyclic strain, mechanical stimulation had a specific role in inducing Hic-5 association with the cytoskeleton. Identification of 12 Hic-5 isoforms ( 31 ) may explain the range of biological responses attributed to Hic-5 and complicates interpretation of its role in mechanotransduction.

A fraction of PYK2 is associated Hic-5 nevertheless a large fraction of PYK2 remained in the cytoplasm or associated with focal contact proteins such as FAK, explaining that it was not possible to identify PYK2 associated with fibrillar structures of cytoskeleton such as f-actin fibers. We observed a strengthening of PYK2/FAK association under mechanical strain and in a previous study we found a critical role of PYK2 in the late activation of the MAP Kinases cascades (3). Interestingly, it was previously shown that FAK is a PYK2 substrate and that the tyrosine phosphorylation of FAK by PYK2 occurs at sites different from those necessary for the activation of the Grb2/Sos/MAPkinase pathway [START_REF] Li | Interactions between two cytoskeleton-associated tyrosine kinases: calcium-dependent tyrosine kinase and focal adhesion tyrosine kinase[END_REF]. The reinforcement of PYK2/FAK complex might facilitate phosphorylation of FAK and recruitment of other signalling proteins within focal contact such as Src or Fyn ( 32 ).

In summary, we showed that mechanical strain activated two homologue tyrosine kinases, PYK2 and FAK that are both involved in integrin signalling. Moreover, PYK2, which can also be activated in response to a variety of agonists, hormones, or ion channel activation, was found to be specifically associated to different proteins under strain depending of cell compartments. We showed PYK2 associated with Hic-5 in cytoplasmic compartement and with FAK at focal adhesion sites in strained cells (Fig. 4). The redistribution of focal contact proteins under mechanical strain suggested a new way of regulation that implied PYK2 both in cytoplasm compartment by severing the paxillin inhibitor Hic-5 and in focal contact by complexing and activating FAK.

In conclusion, as more and more data have been accumulated concerning intracellular signalling pathways of mechanotransduction in osteoblasts ( 33 , 7), roles of individual molecules tend to become more and more obscure. Thus, some integrated studies are desirable to clarify the complicated intracellular signalling pathways as a whole. PYK2 may be an important newcomer in the mechanotranduction field, as it was emphasized for endothelial cells (23), because it may be located at a critical crossing point of multiple signalling pathways.

[ 13 ] C. E. Turner, Paxillin and focal adhesion signalling, Nat Cell Biol 2 (2000) E231-236.

[ 14 ] Z. Weng, J. A. Taylor, C. E. Turner, J. S. Brugge, and C. Seidel-Dugan, Detection of Src homology 3-binding proteins, including paxillin, in normal and v-Src-transformed Balb/c 3T3 cells, J Biol Chem 268 (1993) 14956-14963.

[ 15 ] M. C. Brown, J. A. Perrotta, and C. E. Turner, Identification of LIM3 as the principal determinant of paxillin focal adhesion localization and characterization of a novel motif on paxillin directing vinculin and focal adhesion kinase binding, J Cell Biol 135 (1996) 1109-1123.

[ 16 ] S. M. Thomas, M. Hagel, and C. E. Turner, Characterization of a focal adhesion protein, Hic-5, that shares extensive homology with paxillin, J Cell Sci 112 (Pt 2) (1999) 181-190.

[ 17 ] M. Matsuya, H. Sasaki, H. Aoto, T. Mitaka, K. Nagura, T. Ohba, M. Ishino, S. Takahashi, R. Suzuki, and T. Sasaki, Cell adhesion kinase beta forms a complex with a new member, Hic-5, of proteins localized at focal adhesions, J Biol Chem 273 (1998) 1003-1014.

[ 18 ] M. Shibanuma, J. R. Kim-Kaneyama, K. Ishino, N. Sakamoto, T. Hishiki, K. Yamaguchi, K. Mori, J. Mashimo, and K. Nose, Hic-5 communicates between focal adhesions and the nucleus through oxidant-sensitive nuclear export signal, Mol Biol Cell 14 (2003) 1158-1171.

[ 19 ] J. R. Kim-Kaneyama, W. Suzuki, K. Ichikawa, T. Ohki, Y. Kohno, M. Sata, K. Nose, and M. Shibanuma, Uni-axial stretching regulates intracellular localization of Hic-5 expressed in smooth-muscle cells in vivo, J Cell Sci 118 (2005) 937-949.

[ 20 ] A. E. Aplin, and R. L. Juliano, Regulation of nucleocytoplasmic trafficking by cell adhesion receptors and the cytoskeleton, J Cell Biol 155 (2001) 187-191.

[ 21 ] R. J. Majeska, S. B. Rodan, and G. A. Rodan, Parathyroid hormone-responsive clonal cell lines from rat osteosarcoma, Endocrinology 107 (1980) 1494-1503.

[ 22 ] A. J. Banes, J. Gilbert, D. Taylor, and O. Monbureau, A new vacuum-operated stressproviding instrument that applies static or variable duration cyclic tension or compression to cells in vitro, J Cell Sci 75 (1985) 35-42.. [ 24 ] N. Nishiya, K. Tachibana, M. Shibanuma, J. I. Mashimo, and K. Nose, Hic-5-reduced cell spreading on fibronectin: competitive effects between paxillin and Hic-5 through interaction with focal adhesion kinase, Mol Cell Biol 21 (2001) 5332-5345.

[ 25 ] N. Nishiya, T. Shirai, W. Suzuki, and K. Nose, Hic-5 interacts with GIT1 with a different binding mode from paxillin, J Biochem (Tokyo) 132 (2002) 279-289.

[ 26 ] Y. Shikata, K. G. Birukov, A. A. Birukova, A. Verin, and J. G. Garcia, Involvement of site-specific FAK phosphorylation in sphingosine-1 phosphate-and thrombin-induced focal adhesion remodeling: role of Src and GIT, Faseb J 17 (2003) 2240-2249. . We observed that in controls and immediately after strain the four proteins were localized at focal contacts. Whatever the timing, Paxillin and FAK remained associated with focal contact proteins, this is in sharp contrast with the redistribution found for HIC-5 that is found cytoplasmic as soon as 30' after strain and clearly associated with fibrillar structures of the cytoskeleton 240 minutes after strain. As for PYK2 wich presented a diffuse (cytoplasmic) and focal contact pattern at 0' and 240', we observed a complete diffusion of the staining 30' after strain. Bar 10 µm. Subconfluent monolayers of ROS17/2.8 were subjected to cyclic strain. Cells were then fixed and immunostained 30 minutes (30') or 240 minutes (240') after strain with anti-Hic-5. Same field is illustrated in (A and B), Visualisation of Hic-5 in the nuclear plane (Fig. 3A) illustrated that Hic-5 was not present is the nucleus and that punctuated staining observed 30' after cyclic strain were detected in apical structures of the cells (Fig. 3B). Hic-5 staining 240' after strain illustrated that Hic-5 associated with fibrilllar structures (white arrows) (Fig. 3C).

Bars: 10 µm. Lysates from ROS 17/2.8 were immunoprecipitated using anti-PYK2 (A, C, D) or anti-Hic-5 (B) antibodies. The immune complexes were then Western-blotted with anti-Hic-5, antipaxillin or anti-FAK antibodies as indicated. We found that under cyclic strain, PYK2 increased its association with FAK, and HIC-5 at the expense of HIC-5/Paxillin complex.

  and PYK2 from lysates of static and stretched cells and probed with anti-phosphotyrosine antibody. FAK phosphorylation increased in a time dependent manner (Fig 1B). As for PYK2, its phosphorylation increased immediately after strain (Fig 1C) and persisted after 4h. We then immunoprecipitated Paxillin and Hic-5 from lysates of static and stretched cells and probed with anti-phosphotyrosine antibody. High levels of Paxillin phosphorylation began immediately after strain (Fig 1D) as well as Hic-5 and remained at the same level at 4h (Fig 1E).

[

  23 ] P. F. Davies, Multiple signaling pathways in flow-mediated endothelial mechanotransduction: PYK-ing the right location, Arterioscler Thromb Vasc Biol 22 (2002) 1755-1757.

Figure 1 :

 1 Figure 1: Tyrosine phosphorylation of focal contact proteins induced by cyclic strain.

Figure 2 :

 2 Figure 2: Microscopic views of Paxillin, FAK, HIC-5 and PYK2 immunostaining in

Figure 3 :

 3 Figure 3: Microscopic views of HIC-5 30' and 240' after cyclic strain.

Figure 4 :

 4 Figure 4: Strain-induced modification of PYK2-containing complexes.

Figure 5 :

 5 Figure 5: Proposed mechanism of focal contact activation.

ACKNOWLEDGEMENTS

This study was supported by ERISTO (European Research in Space and Terrestrial Osteoporosis) contract number 14232/00/NL/SH and INSERM (Institut National de la Santé et de la Recherche Médicale).


Guillaume Lamé
email: guillaume.lame@ecp.fr

Tu-Anh Duong

Marija Jankovic

Julie Stal-Le Cardinal

Oualid Jouini

Analysis of Implementation of Care Coordination in a Multi-Level Care Provider Organization: a Need for Systems Approaches

Better care coordination is a crucial objective to answer to the rising complexity of healthcare and the associated increase in costs. Process-based organizations is a widely recommended method for achieving this goal.

In this article an initiative of implementing a care process in a French public hospital group is analyzed. The procedure to design the care process is documented and the official care process is compared to the current situation in a hospital. This analysis shows how important local parameters are in such projects. The shortcomings of the approach are identified and propositions to overcome these issues are made.

Introduction

Health care systems around the world are under pressure. As life expectancy is increasing and chronic diseases are getting more frequent, demand is rising but national expenditure is not rising as fast [START_REF]OECD: Health at a glance 2013: OECD Indicators[END_REF]. Therefore there is a clear need for productivity increase. In France, hospitals have been identified as one of the sources of increase of global efficiency [START_REF]Cour des Comptes: La Sécurité sociale -Rapport sur l'application des lois de financement de la sécurité sociale[END_REF]. However, in the same time, care complexity is continuously increasing [START_REF] Plsek | The challenge of complexity in health care[END_REF], and hospitals have longsince been identified as complex organizations [START_REF] Georgopoulos | The American General Hospital as a Complex Social System[END_REF]. In this ever-increasing complexity, sources of productivity need to be identified and efficiency losses need to be addressed.

To deal with this situation, organ-based silo organizations are no longer adequate and better care coordination should be attained [START_REF] Glouberman | Managing the care of health and the cure of disease--Part II: Integration[END_REF]. Systems engineering approaches have been identified as a way forward [START_REF] Reid | A Framework for a Systems Approach to Health Care Delivery. In: Building a Better Delivery System: A New Engineering/Health Care Partnership[END_REF], and as a part of this process-based organizations have been promoted to achieve better coordination. Consequently, hospitals have started to shift towards more process-oriented organizations by designing care processes. However, social scientists have shown that theoretical organizations and real-life events are not the same thing [START_REF] Dupuy | Lost in management: la vie quotidienne des entreprises au XXIe siècle[END_REF]. More particularly Nyssen [START_REF] Nyssen | Coordination in hospitals: organized or emergent process?[END_REF] shows that real-time care coordination can be an "emergence-through-use" phenomenon. The intent of the designer of the management procedures and the behavior of the real system can be two very different things.

In this context, the objective is to achieve coordination by design in order to have more robust and predictable coordination mechanisms. How can this be achieved? To answer this question, an initiative from a French care provider is studied in this article. It is a top-down project aiming at the implementation of an integrated care process for cancer care. The coordination mechanism "as designed" is compared to the situation "as happening". Dates of main events are gathered from medical records to build a picture of the real current situation. This situation is confronted with the desired model.

Conclusions are drawn for the design of coordination-enabling systems and processes and the management of large complex organizational systems. Centralized and non-differentiated initiatives have poor chances of success. In this case, taking into account the diversity of cancer types and organizations is crucial.

2 Context and literature review: care coordination

Care coordination

Care coordination has been defined as "the deliberate organization of patient care activities between two or more participants (including the patient) involved in a patient's care to facilitate the appropriate delivery of health care services." [START_REF] Mcdonald | Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies (Vol. 7: Care Coordination)[END_REF] It includes resource management and is often achieved through information exchanges. To achieve this, process-oriented care organizations have been proposed as a solution [START_REF] Vera | Process-based organization design and hospital efficiency[END_REF]. Different approaches exist to implement process-based care organizations, which can be classified in two broad categories [START_REF] Axelsson | Organizing integrated care in a university hospital: application of a conceptual framework[END_REF]: an "industrial" approach based on methods such as lean management, total quality management and business process reengineering [START_REF] Ben-Tovim | Patient journeys: the process of clinical redesign[END_REF]; and the "integrated care" stream, coming from the medical world, with a strong emphasis on evidence-based medicine [START_REF] Axelsson | Organizing integrated care in a university hospital: application of a conceptual framework[END_REF][START_REF] Vanhaecht | The Impact of Clinical Pathways on the Organisation of Care Processes[END_REF]. The organization studied here applied the "integrated care" approach, although evidence is limited on the efficiency of such a method (Vanhaecht shows that integrated care pathways improve some aspects of care coordination [START_REF] Vanhaecht | The Impact of Clinical Pathways on the Organisation of Care Processes[END_REF], but other researchers exhibit mixed results for clinical pathways initiatives [START_REF] Panella | Reducing clinical variations with clinical pathways: do pathways work?[END_REF][START_REF] Dy | Critical Pathway Effectiveness: Assessing the Impact of Patient, Hospital Care, and Pathway Characteristics Using Qualitative Comparative Analysis[END_REF]).

French context for cancer care coordination

In France, cancer care coordination is organized as a multi-level system. Table 1 shows the different levels of care coordination at the national and regional levels and for the case of the care provider and the hospital at study. This provider is a public grouping of university hospitals, hospitals and clinics. It has elaborated a cancer strategy to comply with national and regional directives and to maintain its leadership on cancer care and research. This strategy is informed by a cancer working group at the head of the organization. Expert centers are certified in the member-hospitals of the provider. This certification is an acknowledgement of their excellence for care and research. As part of its cancer strategy, the provider has launched an initiative to improve its organization for providing cancer care. This initiative is related to the "integrated care pathways" concept. A care process has been designed for implementation in all member hospitals, and indicators have been defined to manage this process.

In this study the objective is to analyze this project and contrast it with systems engineering perspectives. Indeed, previous studies have shown limited adherence to clinical pathways [START_REF] Klundert | Measuring clinical pathway adherence[END_REF] and mixed results when comparing theoretical processes with real-life events [START_REF] Dupuy | Lost in management: la vie quotidienne des entreprises au XXIe siècle[END_REF][START_REF] Nyssen | Coordination in hospitals: organized or emergent process?[END_REF], which raises questions on the approach used.

Usually, systems engineering starts with the analysis of context, environment, shareholders and objectives. Then specifications are established for the system. Finally processes are designed [START_REF] Walden | International Council on Systems Engineering eds: Systems engineering handbook: a guide for system life cycle processes and activities[END_REF]. This phase is top-down, from the system towards its elements. The design of the care process is documented and situation at the operational level, i.e. the "down" part of this top-down initiative, is analyzed to draw conclusions on the approach used.

Methods

First, a qualitative study is conducted to understand how the process for cancer care was designed. This analysis is performed by document analysis and a 45 minutes semi-directed interview with the head of the oncology department at the studied hospital, who was also a member of the process design project team.

Then data is analyzed for some patients in the hospital. Two cancer types are targeted: prostate cancer and pancreas cancer. This choice is made based on data-availability and number of patients treated at the hospital. For these two types of cancer, patient records are analyzed based on the following criteria:

-All patients treated for the first time between January and June 2014 and coded in a Diagnosis-Related Group of prostate cancer or pancreas cancer -Both inpatient and outpatient treatment were considered -Patients who have been treated for cancer in the 3 previous years are excluded Data comes from three sources: the medical records management system, the appointment scheduling system, and the Diagnosis-Related-Group payment management system. Following information is gathered:

-Age, ID, cancer code

-

Materials and results

Qualitative study: process design and implementation

The analysis of the documents produced by the process design team and the interview with the oncology professor provide a good understanding of the care process that was designed and the way it was designed. The cancer care process itself is pictured in figure 1. It is structured in four phases: entrance in the system, diagnosis, treatment and "after-care". It specifies a set of guiding principles:

-Cancer announcement should be done in two steps: one for diagnosis announcement, and one for treatment announcement -These two announcement steps should be two different consults -Between these two consults, treatment should be discussed in a multidisciplinary meeting, with at least three different medical specialties (e.g. urologist, oncologist and radiotherapist) Six delay indicators are defined on this process. They are described in table 2. This process is at a very high level. Figure 2 shows how it was designed.

Fig. 2. design project

First, all expert centers were asked to draw a model of the care process for their specialty (e.g. urology cancers or blood cancers). No common formalism was provided, so various level of details were obtained. All the processes modelled by the expert centers were synthesized at the top-level of the provider in a mixed descriptive-prescriptive way which created the final care process of figure 1. KPIs were also defined at this stage. Then this process and its indicators were transmitted down to hospitals. A first KPI measurement was performed, where not all hospitals were able to measure all KPIs. The results were transmitted to the top level. Current thinking in the project group is on whether six KPIs is not too much and which KPIs could be deleted from the list.

Concerning the implementation of this process, in our hospital no resources have been allocated to this project. KPIs are not routinely computed. This will allow us to study the "real system" before implementation of this new procedure.

Quantitative study: current situation in the hospital

Two cancer types are studied: prostate and pancreas. For prostate cancer, 120 candidates are identified for inclusion. However, after the medical records have been analyzed, only 70 are included. For pancreas cancer, from 39 candidates 21 patients are included. Details are provided in table 3. The types of treatment are also very different: mostly surgery for prostate cancer patients, chemotherapy and palliative care for pancreas cancer patients. Survival rates are completely different.

Finally, ways of entrance in the hospital also differ: most prostate cancer patients are detected through a prevention scheme, whereas there is no such protocol for pancreas cancer and most patients come for abdominal pains or other symptoms that need to be related to pancreas cancer.

As the number of included patients is low for pancreas cancer, only prostate cancer will be analyzed further. Two interesting comparisons can be made: with the provider-level process, and with national data. Table 4 shows delays computed for prostate cancer patients in the hospital (hosp.) and corresponding delays from a national investigation undertaken by the national cancer institute, INCa [START_REF]INCa: Délais de prise en charge des quatre cancers les plus fréquents dans plusieurs régions de France en 2011 et 2012 : sein, poumon, côlon et prostate[END_REF]. This investigation included both general hospitals and university hospitals, from the public and private sector, in 17 French regions (which cover almost 50% of the French population).

Ratio of negative results

Hosp. 0% 55% 55%

INCa 3% 25% 9%
For mean and median computation, only positive values are included. They show that time from biopsy report to MDM is shorter in this hospital than nationwide. However, delays from MDM to surgery are longer in this hospital.

But the main comment that can be made on these results is on the ratio of negative results (the proportion of negative delays for all included patients). For the delay from MDM to surgery, this ratio is of 55% in this hospital, and 25% nationwide. It means that most patient get their surgery, and their case is discussed in the MDM only after that, when treatment has already been performed. This goes against the recommendations of the provider-level process. It also appears that surgery rates are much higher in this hospital (91% of patients) than nationwide (49% of cases in the INCa study).

Some additional treatment can be performed. For patients who had surgery, if no biopsy is performed at the hospital (which means that they already had biopsy results when they arrived), the delay between the first appointment and the treatment is significantly shorter (Student's t-test, unilateral, p < 0.001, 38 observations with biopsy at the hospital, 32 without). Also the relation between Gleason score and time to treatment can be analyzed. It shows that for Gleason scores 8, 9 and 10 (the most aggressive tumors), the delay between first appointment and treatment is significantly shorter than for Gleason scores 7 (Students t-test, unilateral, p < 0.01, 51 observations with Gleason 7, 12 with Gleason above 7). Therefore, if the diagnosis is clear from the beginning, time to treatment is faster, and the more serious the tumor the shorter the time to treatment. This is what would be expected.

Discussion

Global project and local specificities

Although patient record analysis is a long process (about a full week of work for one person to analyze the 159 records), a lot of data can be extracted. However, it is not clear how to make sense of this data.

A first point is surgery rates for prostate cancer. It is much higher in this hospital than nationwide. Nevertheless, the national study includes patients who were in the first steps of cancer and were put under surveillance. These "early" patients don't get hospitalized.

A second point is the rate of negative delays between MDM and treatment. One reaction could be to blame the hospital studied here: it is not following recommendations. However, this hospital has a well-known expertise for prostate surgery. It has some very specific equipment that make it a reference center for this type of intervention. Probably people come to this hospital for this reason: they choose surgery as a treatment with their private practitioner, and then go to this famous reference center. The surgeon only follows the patient's decision, for a surgery that has become almost a routine operation. These cases may also have been discussed in a MDM in another organization, after which the patient chose to be treated in this reference center.

Delays are another element to look at. Time to surgery can be longer or shorter (here it is difficult to say due to the high rate of negative delays), but it will depend on the population addressed by the hospital. The performed analysis shows that the more aggressive the tumor, the shorter the time to treatment. Delays depend on the severity of the patient's condition, which is understandable. Hospitals should therefore not be compared on this indicator. But even for one hospital, is this indicator supposed to rise or decrease? Actually, setting an objective could lead to counterproductive measures where the time from MDM to surgery is reduced on average but increased for more urgent patients.

All these elements (negative delays from MDM to surgery and high surgery rates due to hospital specialization and reputation, delays whose interpretation is uncertain) point to the specificity of each situation. Local contexts need to be taken into account to create relevant processes and indicators. Characteristics of this local context that need to be paid attention to include:

- Here, indicators could be associated to objectives, but these objectives would not reflect the complexity of the situation.

The comparison of prostate cancer and pancreas cancer is also instructive. It shows that treatments are very different for these two types of cancer, in the same organization: surgery is the main treatment for prostate cancer in the studied hospital, chemotherapy or palliative care for pancreas cancer.

The analysis performed and a discussion with practitioners showed that the uncertainty of the diagnosis is very different in these two cases. Pancreas cancer can go unnoticed for a while, and patients often come to the hospital with an advanced cancer. On the other hand, prostate cancer evolves more slowly, it has a nationwide detection scheme, and prostate surgery seems to have become a more routine operation in this hospital due to the large number of cases treated.

Therefore disease complexity should also be considered when establishing processes or indicators.

Procedures can be more or less complex: standard, routine or non-routine [START_REF] Lillrank | Standard, routine and non-routine processes in health care[END_REF]. Van der Geer et al. [START_REF] Van Der Geer | Performance management in healthcare: Performance indicator development, task uncertainty, and types of performance indicators[END_REF] have shown that when they are given the opportunity to develop their own performance indicators, medical teams obtain different results depending on the uncertainty of the tasks and diseases. Therefore defining common indicators for these two types of cancer appears very challenging as the activities measured should not be the same: problem-solving for pancreas-cancer, treatment and outcomes for prostate cancer.

Vertical (across hierarchies), horizontal (across domain specialties) and longitudinal (along time) integration are needed [START_REF] Nyssen | Coordination in hospitals: organized or emergent process?[END_REF] and should always take into consideration the complexity of local operations. Complexity can be described in three dimensions: diversity, multiplicity and interconnectedness [START_REF] Jacobs | Complexity: Toward an empirical measure[END_REF]. In this case multiplicity has been considered but the importance of the diversity of patients, disease characteristics and organizations has been underestimated. Besides, interconnectedness between organizations characteristics and patient profiles has also been forgotten.

These considerations are at the heart of complex systems engineering. One of the conclusions is that systems engineering could help as it starts with the analysis of goals and context, then specifies the system before actually designing it. Here context analysis and goals of different shareholder have not been given enough attention which is why results are not as useful as hoped. When gathering information on current practices, specifications on process models were not given to expert centers, which is one of the reasons why the final unified process model was hard to design. -Cancer types are differentiated at the top level, as they constitute different diseases with different care strategies and challenges. Horizontal integration must be achieved types if a generic metric for cancer care is desired.

-Comparisons between lower-level elements are possible at each level, but the metrics are not necessarily the same at each level. This is related to the difference between tall organizational complexity and symmetric organizational complexity defined by Burton, De Sanctis and Obel [START_REF] Burton | Organizational design a step-by-step approach[END_REF]. Tall organizational complexities are fit for functional configurations in varied but predictable environments. Symmetric complexity is needed for turbulent (varied and hardly predictable) environments with matrix organizations: here, medical departments and care process across these departments.

Fig. 1 .

 1 Fig. 1. Cancer care process

  Hospital specialization in one technique or another -Hospital or physician reputation -Population addressed -Type of organization

Fig. 3 .

 3 Fig. 3. Vertical and horizontal integration for cancer care in France: proposed framework Figure 3 shows a proposition of integration scheme for cancer care in the provider studied here. It differs from the current architecture:

Table 1 .

 1 Levels of cancer care coordination in France

	Level	Actions and responsibilities	Figures
	France	Plan Cancer 2014-19: strategy and objectives	3 million patients
		National Cancer Institute (INCa): recommendations and	355.000 new cases / y
		certification	148.000 deaths / y
	Regional	Transcription of national directives into regional policy
	health

  Cancer characteristics: metastatic or not, diagnosis (with biopsy results) available at first consult or not, additional exams needed or not, first Gleason score measured for prostate cancer (Gleason score measures the aggressiveness of a tumor. The higher the Gleason score, the worse the prognosis.) -Date of the first multidisciplinary meeting where the case was discussed -Date of the biopsy and date of the biopsy report, dates and types of treatments -Date of apparition of metastasis if relevant, date of decease if relevant -Number of consults, number of hospital stays, departments involved in the care As this was the first study of this type, information is extracted manually.

Date and department of the first appointment, date of announcement consult -

Table 2 .

 2 KPIs for the cancer care process

	#	From	To
	D1	Scheduling of first appointment	First appointment
	D2	First appointment	Multidisciplinary Meeting (MDM)
	D3	First appointment	First treatment
	D4	Date of biopsy	Biopsy report

Table 3 .

 3 Type of treatment received for prostate cancer care

		Prostate		Pancreas
	Inclusion	% of cand.	#	% of cand.	#
	Candidates for inclusion	100%	120	100%	39
	Patients included	58%	70	54%	21
	Wrong coding	23%	27	28%	11

These two populations are very different. They don't use the same resources: on average, pancreas cancer patients transit through 3.3 departments, which is more than twice the number of departments for prostate cancer patients.

Table 4 .

 4 Delays for prostate cancer care (MDM: multidisciplinary meeting)

			For all patients	If surgery is performed
			Biopsy report to	MDM to surgery	Biopsy report to
			MDM (days)	(days)	surgery (days)
	Number	Hosp.	70	63	63

Strengths and limitations

In this study, medical records for a 6-months period are analyzed. This analysis provides insights on how operations are currently performed, and how they are thought of at the top-level: the "bottomup view" of a "top-down" initiative.

However, the low number of patients for pancreas cancer did not allow much analysis on this population. Almost half of the candidate pancreas cancer patients could not be included. This relates to the more global issue of data access. This problem has already been identified in France [START_REF]INCa: Délais de prise en charge des quatre cancers les plus fréquents dans plusieurs régions de France en 2011 et 2012 : sein, poumon, côlon et prostate[END_REF] and other countries [START_REF] Zegers | Quality of patient record keeping: an indicator of the quality of care?[END_REF]. Data is hard to access as it is available in the form of free-text in medical records rather than in a database. It is also scattered between different information systems, and the reliability of data in these systems is not optimal as wrong coding is common.

Future developments

This study underlines the shortcomings of centralized, top-down approaches to the management and coordination of a complex system such as a group of hospitals. In this multi-level complex system, local situations are different and require differentiated approaches. Complex organizational systems theory and network analysis can be of great help.

The analysis of patient journeys for prostate cancer care and pancreas cancer care has shown that inside each cancer type different trajectories coexist. However, these trajectories are not readily available: patient data needs to be analyzed so that relevant patient groups can be identified. Data analysis methods such as Classification And Regression Tree analysis have already been used for operations research in healthcare [START_REF] Harper | A framework for operational modelling of hospital resources[END_REF]. They could be used to cluster patients for care coordination. For each of these groups of patients, an assessment of the coordination needs of the patients and the organization needs to be performed, so that appropriate resources can be allocated and other actions can be taken (reshape multidisciplinary teams, work on information systems…).

Finally, for such large systems as this health provider, "handmade" process mining is not enough and automated methods must be developed. However, hospital information systems are particularly divided and make this quite difficult.