Busness, Management and Educaton ISSN 2029-7491 prnt / ISSN 2029-6169 onlne 2013, 11(2): 256 280 do:10.3846/bme.2013.15 applyng the prorty dstrbuton method for EMPLOYEE motvaton Jonas Žaptorus Vlnus Gedmnas Techncal Unversty, Saulėteko al. 11, LT-10223 Vlnus, Lthuana E-mals: jonas.zaptorus@vgtu.lt Receved 26 August 2013; accepted 27 September 2013 Abstract. In an age of ncreasng healthcare expendture, the effcency of healthcare servces s a burnng ssue. Ths paper deals wth the creaton of a performancerelated remuneraton system, whch would meet requrements for effcency and sustanable qualty. In real world scenaros, t s dffcult to create an objectve and transparent employee performance evaluaton model dealng wth both qualtatve and quanttatve crtera. To acheve these goals, the use of decson support methods s suggested and analysed. The systematc approach of practcal applcaton of the Prorty Dstrbuton Method to healthcare provder organsatons s created and descrbed. Keywords: remuneraton scheme, performance-related pay, parwse comparson method, healthcare provder organsatons, decson support methods, data mnng applcaton. Reference to ths paper should be made as follows: Žaptorus, J. 2013. Applyng the prorty dstrbuton method for employee motvaton, Busness, Management and Educaton 11(2): 256 280. http://dx.do.org/bme.2013.15 Jel Classfcaton: C31, C81, I11, J28, J3. 1. Introducton Ths artcle addresses the ssue regardng the use of a fnancal employee motvaton model based on measured performance and ndvdual value-added n the healthcare sector. An overvew of early and contemporary theores of motvaton factors shows that dependng on the way t s used, motvaton can nfluence nternal characterstcs and external behavours of employees and affect ther performance (Abramson, Inglehart 1995; Martnkus, Savanevčenė 1996). It should be noted that many forms of motvaton exst and not all of them lead to the same results. The choce of motvaton nstruments depends on ndustry, company polces, employee job profle characterstcs and other factors. In each organsaton, ts remuneraton system forms the foundaton of a mult-layered motvatonal system. Besdes, t must be far, equtable, consstent and transparent. In addton, performance-related pay must be based on accomplshments of an ndvdual employee or jont results of the team, provded efforts of separate employees are mpossble to measure. Copyrght 2013 Vlnus Gedmnas Techncal Unversty (VGTU) Press Technka www.bme.vgtu.lt
Busness, Management and Educaton, 2013, 11(2): 256 280 Performance or work output based employee motvaton systems are used n many domans. The prerequste for performance-related remuneraton s the ablty to defne regularly measurable work results and ther qualtatve parameters. By lnkng employee pay to ndvdual and teamwork results, managers can use the remuneraton system to promote hgh performance culture, teamwork and foster other organzatonal objectves. The creaton of a fnancal employee motvaton model s a complex mult-level endeavour, whch may nfluence busness results of an organsaton. By mplementng a fnancal motvaton system, organsatons harness two competng nterests: on the one hand, concerned wth maxmsaton of ther pay employees become nterested n mprovng ther work results; whle on the other hand, the employer s nterested n cost savngs. Snce ancent tmes, varous remuneraton systems have been created to ensure cost-effectveness, employee motvaton and socal balance. The man remuneraton system types are tme-based (basc pay for standard hours) and unt-based, also called pece rate reward systems. Addtonally, employers may use bonus systems such as addtonal hours reward, sales commsson, and proft-related. Numerous varatons and combnatons are avalable dependng on an ndustry or a job profle. In terms of unt-based forms of remuneraton schemes, employees have an ncentve to ncrease labour productvty, whch n turn leads to hgher pay. In the healthcare doman, ths type of payment s drectly lnked to the most popular rembursement model, namely Pay-for-Servce. It s heavly used by prvate healthcare provder organzatons (HPO) worldwde, partcularly n the US. Indrect unt-based remuneraton s charactersed by ndrect work results of an employee. In ths nstance, performance related pay of support staff s lnked to achevements of the entre team; e.g. the varable salary porton of an operatonal theatre nurse may depend on the overall performance of the team. However, n most publc and some prvate HPOs, the fnancal model of an organsaton s rarely transposed nto the remuneraton scheme; consequently, tme-based remuneraton s typcally used. As European countres have a hgher share of publc HPOs, the most common form of payment s a tme-based salary system, where amount pad s a functon of hours worked and employee qualfcatons. The smplest tme-based form of payment s the unfed payment for work tme system, whch s a fxed basc pay for standard hours. Employee qualfcaton requrements and job profle complexty s perceved dfferently n dfferent countres, ndustres and even competng companes. А set of defnng crtera ncludes all factors affectng job characterstcs and condtons. Such crtera set may nclude the requred level of educaton, cooperaton, concentraton, unversalty and workng condtons (Kahya 2007; Pogg 2010; Katskea, Theodosou, Perdks, Kehagas 2011). Ths paper provdes an overvew on regulaton of labour relatons through performance-related payment schemes, whch am to ensure cost-effectveness, employee motvaton and socal balance. Ths sgnfcantly ncreases the mportance of the human 257
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton factor, wth the focus on personal responsblty, operatonal effcency and contnuous mprovement processes. The practcal mplementaton of performance-related payment models n an organsaton has three steps: plannng, mplementaton and montorng of the new remuneraton model. The plannng step conssts of determnaton of performance ndcators to be used n the model; creaton of a calculaton model for performance related pay; dscusson and communcaton wth personnel. The mplementaton step conssts of the actual mplementaton of new accountancy polces, performance measurements and changes to Human Resource (HR) polces. The montorng step s a routne actvty amng to montor and analyse changes n an organsaton caused by an mplemented employee remuneraton model. Ths artcle covers plannng, executon and montorng steps, excludng the HR related actvtes assocated wth communcaton, legslaton and fnancng. In the second secton, the author analyses the current stuaton n the healthcare sector and the latest trends n remuneraton models used. Based on the analyss, a mult-crtera decson support method s proposed for the desgn of a performance related remuneraton model for HPOs. In the followng sectons, the artcle descrbes the Prorty Dstrbuton Method (PDM) and showcases ts use by npatent healthcare provders. Fnally, t proposes methods for determnaton of performance ndcators to be used n PDM, ncludng decson support and data mnng, as well as technques for subsequent montorng of acheved results. The artcle offers an llustraton on the use of descrbed methods n healthcare provder organsatons and evaluaton of the value of each job profle, consderng subjectve and objectve socal factors, whch affect the salary. 2. Remuneraton scheme for medcal professonals Currently, a number of substantally dfferent fnancal models are used n healthcare worldwde. Each of them proposes a dfferent busness model for healthcare provders. Nevertheless, fee-for-servce, per capta payment and pay-for-performance are the most frequent major rembursement methods. Regardless of the fnancal model, a publc or prvate nsurance entty remburses all legal medcal servces provded to a patent, provded they fall wthn nsurance coverage. In some cases, healthcare organsatons receve fxed payments for each patent regstered wth that partcular servce provder. Typcal for prmary care, ths model s used n the UK, US, post-sovet countres, etc. Pay-for-performance model s usually used by nsurance agences as a bonus, provded a healthcare faclty meets certan qualty and performance requrements. 258
Busness, Management and Educaton, 2013, 11(2): 256 280 Fg. 1. Healthcare expendture growth (Source: Health at a Glance 2011) In the era of steady healthcare expendture growth (Health at a Glance 2011), whch s llustrated n Fg. 1, socety demands better effcency from healthcare provders. Thus, healthcare polcy makers are lookng for systematc changes that would result n better qualty of servces, more effcent healthcare provders and a healther populaton for less money. Ths s a truly complcated challenge; however, some recent examples of dfferent ntatves amed at tacklng chronc problems of healthcare systems do exst. For example, a new fnancal model for healthcare provders ACO (Accountable Care Organzatons) has been recently ntroduced n the US. It ams to motvate provders fnancally by settng metrcs for qualtatve factors and overall performance. Ths model complements the fee-for-servce model wth a performance bonus based on qualty and cost savngs. Some European countres have ntroduced specal programmes n order to encourage early detecton and preventon of dseases such as dabetes, tuberculoss and HIS as well as breast, prostate and lung cancers. Dfferent fnancal ncentve systems are used to encourage healthcare provders to partcpate n these programs. Gettng better results from doctors and nurses requres actve performance montorng and management. Dfferent contract types and bonus packages have been used to mprove the qualty of servces provded by medcal professonals. Payments based on the fee-for-servce method have caused justfed concerns regardng the delvery of medcally necessary servces and led to unjustfed admssons as well as other problems (Lee, Mongan 2009). However, tme-based salary does not lead to effcent work and encourages lower output. Most nnovatve healthcare provders ntroduce payment mechansms that combne ncentvsed output and qualty outcomes (Darves 2011). Examples are known where up to 20 per cent of doctor salares are performance related, wth nearly half beng lnked to team performance and qualty mprovement measurable values (Paulus et al. 2008). At top class HPO Kaser Permanente, doctors are montored and ranked n real tme on a wde varety of clncal outcomes (Paulus et al. 2008). The 259
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton montorng data s mmedately avalable, so doctors can compare ther personal results wth those of peers n ther group or even across the regon. Not only doctors are subject to changes antcpated n the feld of fnancal ncentves. Nursng personnel s typcally the most populous group of professonals n healthcare, and ther contrbuton s an essental component to achevng mproved productvty, better qualty of care and hgher effectveness n the health sector (Buchan, Black 2011). Wth regard to salares of medcal professonals, rembursement methods used by HPOs have a dfferent nfluence on remuneraton schemes. Frstly, there are dfferent fnancal motvators drven by these methods. Fee-for-servce fnancally encourages hgh output of servces provded to a patent, per capta payment fnancally rewards mnmsaton of servces provded, whle only pay-for-performance method seeks for long-term and hgh-qualty results. Naturally, complex coexstng fnancal models result n a number of dfferent models for remuneraton of medcal employees. However, n practce, two most popular payment forms persst, namely: tme-based fxed salary n publc HPOs and performance-related salares n prvate healthcare facltes. The performance-related salary scheme s typcally calculated consderng quanttatve results, e.g. number of patent vsts, examnatons, surgeres, etc. In prvate HPOs, employee salares are determned by the followng man factors: amount of servces provded; prce level n the market; and personal contrbuton of an employee. Dfferent countres undergo contnuous reform of ther healthcare systems, and the determnaton of medcal personnel remuneraton scheme n publc HPOs s one of the central ssues. In publc HPOs, salares of medcal professonals are usually tme-based and formally defned by the governng body. Obvously, ths payment method alone does not provde adequate motvaton for hgher qualty or performance. However, usually there are some possbltes to ntroduce bonuses or a performance-related payment method based on ndvdual or teamwork results, whch could be used as fnancal motvaton nstruments. When an employee s contrbuton cannot be expressed n money or as a percentage of revenue, t s consdered a subjectve decson of the employer. In the publc sector, the remuneraton scheme s determned by the job evaluaton system. The Internatonal Labour Organzaton has suggested a job evaluaton system based on four general factors. Each factor has a certan maxmum number of ponts, wth the total amount of four factors equal to 1000 ponts. Тhe maxmum value of 450 ponts s assgned to the work complexty factor. Work complexty s seen as an aggregatve factor of requred professonal educaton and experence, decson magntude and manageral level. Socal value of work can get the maxmum of 220 ponts; t s determned by two crtera: appontment procedures and socal sgnfcance of work. Professonal responsblty has the maxmum of 180 ponts; t s descrbed by three crtera: mpact on safety of other 260
Busness, Management and Educaton, 2013, 11(2): 256 280 people, materal and moral responsblty, and cooperaton wth external organsatons. The last factor s work complexty and work envronment, whch can get the maxmum of 150 ponts; t s charactersed by two crtera: mental and physcal stress, caused by the level of nervous stran at work and workng condtons. Accordng to ths system, each job profle s rated accordng to the aforementoned four factors assgnng ponts. Fnally, totals are calculated and normalsed, and the resultng coeffcent s appled to the offcal mnmum monthly salary. Regardless of the ownershp form of an HPO, and the rembursement model of the healthcare nsttuton, the ntroducton of a balanced performance-related payment scheme for medcal professonals, whch consders both qualtatve and quanttatve factors, may provde an answer to the current effcency problems faced by the healthcare sector. Implementaton of such balanced performance-related remuneraton scheme requres determnaton of measurable ndcators. There s a number of healthcare qualty and performance ndcators that are a part of best practce busness metrcs or governmental programs and legslaton. However, there s a lack of methods for selecton, rankng and weghtng of these ndcators, gatherng them nto one system sutable for fnancal employee performance evaluaton. For ths purpose, t s suggested to use the Prorty Dstrbuton Method, descrbed by Žaptorus n 2006. 3. Selectng performance ndcators The change of the exstng employee remuneraton system of an organsaton should start wth determnaton of performance ndcators to be used n a new model. Typcally, the frst pont of reference would be the lst of key performance ndcators defned by the organsaton tself. However, healthcare sector s usually nfluenced by external forces such as governmental bodes or nsurance companes, whch set fnancal ncentves for meetng certan crtera. Therefore, dependng on the healthcare faclty profle and regon, one can select from among dfferent sources. One of them s the Meanngful Use program (Meanngful use 2013) establshed by the US Department of Health and Human Servces, whch has a set of crtera for organsatons meanngfully usng electronc health record systems. Another ntatve from the US s called Accountable Care Organzatons (ACOs), whch proposes that partcpatng healthcare facltes receve addtonal payments based upon specfed qualty and savngs crtera. Another opton s settng performance ndcators for healthcare provders n legslaton, as t s done n Lthuana by the Mnstry of Health. One can conclude that there s no lack of performance ndcators for the healthcare ndustry; however, there s a lack of methodologes for the selecton of optmal sets of ndcators for a specfc healthcare provder. There s a hgh magntude of HPOs wth dfferent clncal domans and dfferent fnancal schemes. Below, the author proposes a generc method, whch allows an organsaton to analyse and choose performance evaluaton ndcators for a performance-related remuneraton model. 261
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton Step 1: Generate a comprehensve lst of clncal, fnancal and manageral ndcators, derved from the followng sources: KPIs used nternally, HPO performance related ndcators assgned by nsurance companes and HPO performance-related ndcators assgned by government authortes. Step 2: Flter ndcators, whch are practcally measurable and applcable for calculaton of fnancal ncentves, and assgn them to job profles. Afterwards, they wll be used to defne the ndcators value scale, evaluaton perod and method. Step 3: Transform nterrelated ndcators by combnng them. For example, ndcators such as overtme hours per month and number of nght shfts per month can be combned nto a composte ndcator hgher compensated work hours per month. Step 4: Prelmnarly prortse the ndcators (fnal rankng of ndcators wll be made usng the Prorty Dstrbuton Method (PDM) method). The rule of thumb s to gve a hgher prorty to ndcators lnked to the organzaton s strategy and to rase prorty of ndcators that have low performance values. Step 5: Identfy potentally dependable ndcators,.e. ndcators that are defntely dependable from other measurable ndcators, whch were not selected for the fnancal ncentves model. Ths can be acheved manually or by applyng statstcal regresson analyss tools. A wde range of clncal, statstcal and fnancal data avalable n IT systems of an organsaton should be used. The data collected n hosptal nformaton systems (HIS) has a sgnfcant potental for these types of analyses. Step 6: Identfy any specfc factors leadng to unsatsfactory values of selected ndcators. We propose to perform ths knd of analyss applyng data mnng methods, such as assocaton rules analyss based on data prepared n step 5. Let s consder the followng example: an assocaton rules dscovery algorthm was used for data collected from a provder s HIS. One of the rules showed wth hgh confdence a longer average length of stay for patents dagnosed wth hosptal acqured pneumona, whch was developed after usng extra corporeal lung support systems. Consequently, the management decded to ntroduce a specfc performance ndcator related to a careful followng of the defned algorthm and used t for the responsble medcal personnel n approprate wards. Step 7: Based on results obtaned n step 6, update each performance crtera lst n job profles n each organsatonal unt. Step 8: Use the PDM method to rank quanttatve and qualtatve crtera and calculate performance related pay. Data mnng methods can be helpful to determne other mportant ndcators, whch nfluence ntally defned (prmary) ndcators. The beneft of ths type of analyss s automated ntellgent analyss of the aggregated data from dfferent domans: Patent demographcs, clncal patent data; Illness scrpts, ncludng epdemology and average prognoss; 262
Busness, Management and Educaton, 2013, 11(2): 256 280 Computersed physcan order entry systems (CPOE) data; Data collected from nursng charts; Surgery and mnor nterventons protocols; Medcal personnel HR data. For example, usng classfcaton trees (Bellaz, Zupan 2008; Berka, Rauch, Zghed 2009) we can determne what factors nfluence longer Length of Stay (LOS), hgher mortalty rate for specfc nosology, or readmsson rate. Ths approach s sutable for HPOs that have already mplemented HIS and or Electronc Medcal Record (EMR) and that are not lower than STAGE 4 accordng to HIMMS electronc medcal record adopton model (Electronc Medcal Record 2013). Modern HIS, EMR and medcal decson support systems are able to provde vast amounts of data and allow applyng data mnng technques to dscover hdden patterns and dependences as well as facltate route-cause analyss. 4. Prorty dstrbuton method The PDM belongs to the famly of mult-crtera decson support methods, based on expert parwse comparson of crtera. In 1977, Saaty proposed a mult-crtera decson support methodology called the Analytc Herarchy Process (AHP) to rank alternatves by parwse comparson. Ths method requres evaluatng the number of tmes one alternatve (crteron) s better than another one. There are other applcable methods for ths task as well: Smple Addtve Weghtng, TOPSIS (Technque for Order Preference by Smlarty to an Ideal Soluton), to name a few. Each has ts pros and cons; however, hgh practcal applcablty s the strongest feature of the proposed PDM and the reason t was selected. The weakest part of most parwse comparson methods s the dffculty of normalsng the expert opnons. For nstance, defnng the number of tmes mortalty rate n a ward s more mportant than patent acqured post-surgery complcaton s very complcated even for a doman expert. Therefore, t s very helpful to reduce the comparson result range just to three categorcal values as proposed n PDM, namely, less mportant, equally mportant, more mportant. The downsde of PDM s that the method s not mathematcally precse. For a mathematcally proven method, the author recommends a modfed AHP verson, whch addresses the rank reversal problem. Accordng to Žaptorus (2006), the applcaton of the Prorty Dstrbuton Method (PDM) to the fnancal porton of an employee remuneraton package s possble under the followng condtons: employees are workng n teams or shfts and have smlar job profles, a varable salary part or performance bonus are applcable, t s mpossble to drectly and precsely evaluate the productvty of employees. 263
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton PDM s based on expert evaluaton of qualtatve and quanttatve features of an object,.e. one job profle compared to another one. The method allows evaluatng objects, whch have ncomplete or only qualtatve dfferentaton parameters. In practcal settngs, a panel of experts should be formed to analyse ntal data and defne comparson crteron for objects under nvestgaton. The method prortses a group of objects n ascendng or descendng order, dependng on the magntude of ther characterstcs manfestaton, thus calculatng ther ranks. Usng parwse comparsons, the relatve mportance of one crteron over another can be calculated. Accordngly, for each object PDM defnes relatve weghtng, whch expresses the rank of each object s characterstcs and helps to select and prortse the crtera. PDM s flexble n adjustment of precson and degree of justfcaton requred for management tasks and optmal decson support. Typcally, when ndcators wth dfferent orgn and measurement unts exst, the problem arses regardng normalsaton and converson to a unfed measurement unt or non-dmensonal unt. To tackle ths problem, the method proposes the converson of ndcator values to ther relatonal values (ratos), whch are expressed n unform, quanttatve and therefore arthmetcally comparable unts. The ntal step s to defne the most mportant dfferentatng crtera, whch wll be used to calculate performance related payments. There s a number of possbltes for the selecton of crtera, e.g. contractng external HR consultants, surveyng employees and defnng the number of votes, or basng defnton on an ndvdually generated value-added algned wth the company s busness goals and key performance ndcators. As ndcated n the secton Selectng performance ndcators, there s a set of typcal ndcators used n healthcare, some of whch can be successfully projected to job evaluaton ndcators of an ndvdual employee. These specfc healthcare crtera are dscussed n the next secton. There are two potental classes of crtera for evaluaton of productve nput of an employee: quanttatve and qualtatve. Crtera wll be assumed as quanttatve f they are measurable, numercal and ther measurement or evaluaton s not dependent on subject-matter expert opnon, e.g. number of patent vsts, hosptal length of stay, percentage of postoperatve complcatons, and percentage of patent readmssons. In contrast, a qualtatve crteron usually has categorcal values that are ndrectly evaluated by subject-matter experts, e.g. teamwork, dscplne, loyalty, creatvty, or proactvty. Such a qualtatve crteron can be valued, compared to the etalon value f t exsts, or compared to the respectve crteron of other employees n the group or regon. Accordng to the parwse decson rule formulated by Terstown (Beshelev, Gurvch 1974), f a parwse comparson s performed by a group more or equal to 25 ndependent experts then ther evaluaton values have a normal dstrbuton wth varance equal to one. In a practcal settng, the typcal number of experts s less than 25; consequently, dstrbuton s close to normal. 264
Busness, Management and Educaton, 2013, 11(2): 256 280 Let us defne the most mportant crtera set as K{k1, k2, k3, k4, k5}. Each crteron kn should have a defned value range, source, and calculaton method. To rank the crtera we need to defne weght wn of each crteron. In the frame of PDM, t s acheved by comparng crtera n pars. In order to mutually compare kn we wll use the followng table of all possble parwse comparsons: Table 1. Comparson of all possble crteron pars Crtera par Experts 1 2 3 4 5 Average prorty value P^ w1 & w2 w1 & w3 w1 & w4 w1 & w5 w2 & w3 w2 & w4 w2 & w5 w3 & w4 w3 & w5 w4 & w5 All possble ratos of crtera par comparsons are defned by the experts. Ths example analyses smplfed and more practcal comparsons, where the only rato values that can be assgned by the experts are: greater than, equal to, or less than, assumng that the same degree of relatve dfference of crtera pars apples. Then, the comparson matrx A a, j s derved by usng average prorty values P^, and crtera condtonal prortes Pjs are ncrementally calculated. A s a square matrx wth the sze equal to the number of crtera l. As n many mult-crtera decson makng methods that use parwse comparson (Saaty 1977; Uppulur 1989; Wlson, Thabane, Holbrook 2003), the matrx A s naturally recprocal, where aj aj-1. Therefore, only the upper or lower part of t wll be calculated, and another s easly derved. PDM uses formula a,j + aj, 2, wth (1) a, j 0; 2. Accordng to PDM, the followng heurstc s used to derve the comparson matrx. 1 + z, when x x j, a(x ) 1, when x x j, 1 z, when x x, j (2) 265
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton where z s defned as: Kr 1 z + Kr + 1 where: 0.05, l (3) l number of crtera, and K r prelmnary estmated maxmum and mnmum crteron weght rato: K r max mn j X X, (4) where x max and x mn j compared and j ndcators wth a maxmum and mnmum value. By rankng expert ratos values (Table 1), K r 4 can be estmated. Gven the above estmated K r, : 4 1 0.05 z + 0.7 (5) 4+ 1 5 and 1.7, when x x j, a j, 1, when x x j, (6) 0.3, when x x j. Ths derves a comparson prorty matrx A as follows: Table 2. Crtera weght comparson matrx j w 1 w2 w3 w4 5 a w j, b P ' P w1 1 1.7 1.7 1.7 1.7 7.8 37.04 0.348 w2 0.3 1 1.7 1 1.7 5.7 23.60 0.222 w3 0.3 0.3 1 0.3 1.7 3.6 13.10 0.123 w4 0.3 1 1.7 1 1.7 5.7 23.60 0.222 w5 0.3 0.3 0.3 0.3 1 2.2 9.04 0.085 Sum: 106.38 1.000 Consderng the matrx above, the crtera prortes P and then subsequently normalsng P, P has been derved. 266
Busness, Management and Educaton, 2013, 11(2): 256 280 The calculaton s provded below: 1. Calculate prorty sums for each row: l aj, b. j 1 2. Calculate P by summng the product of row prorty a,k and b k : l k k k 1 P a b. (7) 3. Normalse condtonal prortes P values, dvdng P by P : 1 P P ' l. (8) P 1 Wth calculated P values, actual K f r rato s beng calculated and compared to prelmnary estmated rato K r : max f P ' 0.348 Kr 4.094. P'mn 0.085 (9) f Thus, Kr Kr, and we have to algn the ntally calculated z value. The calculaton of correcton coeffcent α: Kr 4,000 α 0,98. f (10) K 4,094 r The Algned z value: z z p α, (11) where z p ntal z value. Thus, z 0.7 0.98 0.69. Consderng the new z value, a new a j valued has been derved: l 1.69, when x x, j a j, j 1, when x x, 0.31, when x x j. The recalculated comparson prorty matrx A s provded below: (12) 267
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton Table 3. Recalculated crtera weght comparson matrx j w 1 w2 w3 w4 5 a w j, b P ' P w1 1 1.69 1.69 1.69 1.69 7.8 36.90 0.345 w2 0.31 1 1.69 1 1.69 5.7 23.60 0.222 w3 0.31 0.31 1 0.31 1.69 3.6 13.34 0.125 w4 0.31 1 1.69 1 1.69 5.7 23.69 0.222 w5 0.31 0.31 0.31 0.31 1 2.2 9.30 0.087 Sum: 106.91 1.000 In the resultng matrx (Table 3), weghted crtera ranks are expressed as normalsed numerc weghts P. The next step s to evaluate employees ndvdually. Quanttatve crtera evaluaton can be drectly performed, applyng normalsed measurement ranges. Indvdual employee crtera rankng wll have the bggest weght value for the best performance value, accordngly, as the bggest weght value for the most mportant crteron was calculated n A. Therefore, f a mnmzng crteron exsts, ts value wll be converted as follows: mnc c, where mnc the smallest value of an object s crteron. c Ths transformaton of mnmsng crtera values wll convert the smallest value to the largest equal to 1. For ndvdual employee s qualtatve crtera evaluaton, PDM wll be appled. External experts or a team of employees should evaluate each employee parwse, accordng to the steps descrbed above. The results of the evaluaton should be combned wth the PDM results of crtera rankng. The complex employee performance value ndcator P,compl. s calculated as follows: P s (1) P s (2) P s (3) P s (4) P s (5) Y 1 Y 2 Y 3 Y 4 Y 5 P, kompl 5;5 S Pj 1; j 1 Y j 268 Fg. 2. Complex employee performance value ndcator
Busness, Management and Educaton, 2013, 11(2): 256 280 where P,compl. -th employee performance value ndcator, P S (j) -th employee evaluaton weght for j-th crteron, y j j-th crteron weght. The employee performance related payment s calculated usng the fxed part of the salary, called the Base. Typcally, the varable part of the salary s formed as a specfc percentage K% of the Base, as defned by company polces. Applyng the calculated complex employee performance value ndcator (Fg. 2), the varable salary part equals to: Salaryvar, Salary fx. K PVI, (13) where Salary var, the varable part of -th employee salary (performance related pay); Salary fx, the fxed part of the -th employee salary. Accordng to Žaptorus (2006), ths method can also be used as a method for evaluaton of an employee job profle. From the pont of vew of HR management, ths heurstc method expresses a comparatve vew of the market value of the job performed by certan employees. The most practcal outcome of the PDM s the defnton of crtera weghts for employee evaluaton, whch can be unversally used n the frame of the analysed company/ department/team. 5. PDM applcaton n healthcare npatent facltes Ths secton wll focus on creatng a performance-related remuneraton model for a hypothetcal npatent healthcare faclty. PDM wll be used to create a performancerelated payment model for physcans and nurses of one hosptal ward. As t was already stated, the ntal step of PDM s to defne ndcators, whch wll be used to evaluate the overall outcome of work. For the sake of ths example, performance ndcators for HPOs approved by the Mnstry of Health (MOH) of the Republc of Lthuana n 2012 (Dėl asmens svekatos prežūros įstagų 2012) wll be used, whch are amed at rasng the overall treatment qualty and becomng a strong complementary evaluaton to the quanttatve metrcs of provded medcal servces. Some of them can be aggregated and successfully projected to performance evaluaton ndcators of an ndvdual employee. To restrct dfferent types of healthcare provders and ther operaton modes, the example wll use ndcators applcable to the general profle hosptals. The followng quanttatve and qualtatve ndcators from the lst of npatent faclty ndcators (Dėl asmens svekatos prežūros įstagų 2012), were selected: 269
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton Table 4. Aggregated ndcators for performance evaluaton approved by MOH Quanttatve crtera Average length of stay Rato of npatent day surgery vsts to overall npatent vsts (ncl. surgery) Mortalty rate Frequency of pressure sores n bedrdden patents Use of dsnfectant lquds Qualtatve crtera Level of patent satsfacton Partcpaton n nternal tranng programs Practced hygene level Addtonally, the followng healthcare qualty and key performance ndcators wll be added: postoperatve complcaton rate; rehosptalsaton rate; medcal errors/clams. Addtonally, the followng non-doman specfc crtera wll be added. Table 5. Generc ndcators measurng employee performance Quanttatve crtera Work hours Shft coeffcent Medcal qualfcaton coeffcent Experence coeffcent Number of non-complance/audt ssues Number of clams Qualtatve crtera Team work orentaton Help to colleagues Dscplne Let s defne the crtera sets for ward physcans and ward nurses combnng both crtera lsts. Job profle crtera for a ward nurse can be defned as follow: Table 6. Performance evaluaton ndcators for a nurse Code Crtera Descrpton k 1 k 2 k 3 k 4 Work hours x shft coeffcent x medcal qualfcaton coeffcent Accumulatve number of regstered ssues and clams per quarter Teamwork ablty (sx months/annual) Personal dscplne (sx months/annual) Composte evaluaton of workload, assumng dfferent ratos for weekday and nght shfts and formally acqured medcal qualfcatons Number of nternal ssues or external clams durng the ongong quarter. Shares nformaton wth colleagues. Ready to help colleagues. Demonstrates postve atttude. Demonstrates problem solvng abltes. Physcan or head nurse orders performed on tme and correspondng to qualty requrements. Documentaton actvtes performed accordng to hosptal rules. 270
Busness, Management and Educaton, 2013, 11(2): 256 280 Code Crtera Descrpton k 5 k 6 k 7 Average quarterly length of stay to average LOS rato Mortalty rate to average mortalty rate rato Frequency of pressure sores n bedrdden patents to average frequency rato Quarterly average patent LOS compared to the natonal or regonal normatve average LOS for the ward specalsaton. Average patent mortalty rate for a perod of sx months or a year compared wth the natonal or regonal normatve average mortalty rate for the ward specalsaton Number of pressure sore ncdents n patents for a perod of sx months of a year k 8 Practced hygene level Quarterly qualty metrc, accordng to a hosptal standard (e.g. use of dsnfectant lquds, hygene qualty checks) k 9 Level of patent satsfacton Qualty metrc defned and dgtsed usng patent surveys for a perod of sx months or a year. k 10 Partcpaton n nternal tranng programs Annual qualty metrc defned as a percentage of partcpaton n nternal tranng programs or ndvdual annual goals. Job profle crtera for a ward physcan can be defned as follow: Table 7. Performance evaluaton ndcators for a ward physcan Code Crtera Descrpton k 1 k 2 k 3 k 4 k 5 k 6 k 7 Work hours x shft coeffcent x medcal qualfcaton coeffcent Accumulatve number of regstered ssues and clams per quarter Teamwork ablty (sx months/annual) Personal dscplne (sx months/annual) Average quarterly length of stay to average LOS rato Mortalty rate to average mortalty rate rato Rate of postoperatve complcatons End of Table 6 Composte evaluaton of workload, assumng dfferent ratos for weekdays and nght shfts and formally acqured medcal qualfcatons Number of nternal ssues or external clams durng the ongong quarter. Shares nformaton wth colleagues. Ready to help colleagues. Demonstrates postve atttude. Demonstrates problem solvng abltes. Orders of superor performance n tme and n qualty. Documentaton of actvtes performed accordng to hosptal rules. Quarterly average patent LOS compared to the natonal or regonal normatve average LOS for the ward specalsaton. Patents mortalty rate for a perod of sx months or a year compared to the natonal or regonal normatve average mortalty rate for the ward specalsaton. Rate of postoperatve complcatons for a perod of sx months or a year compared to the natonal or regonal normatve average rate for the ward specalsaton. 271
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton Code Crtera Descrpton k 8 Rehosptalsaton rate Average rehosptalsaton rate for a perod of sx months of a year compared to the natonal or regonal normatve average rate for the ward specalsaton. k 9 Level of patent satsfacton Qualty metrc defned and dgtalsed through patent surveys for a perod of sx months or a year. k 10 Partcpaton n nternal tranng programs End of Table 7 Annual qualty metrc defned as a percentage of partcpaton n nternal tranng programs or annual ndvdual goals. Parwse comparson as defned n PDM s used to rank and wegh the dentfed crtera. Below, an example of calculatons s provded. These values wll be recalculated for each healthcare nsttuton, amng to apply ths method. As explaned before, the nature of fnancng model used n each partcular faclty wll strongly affect employee motvaton. Therefore, the rankng and weght of the crtera defned wll dffer from one healthcare organzaton to another. As the second PDM step, all defned crtera are compared n pars by the expert panel. The resultng tables of crtera for physcans and nurses are provded below. Table 8. Parwse crtera comparson of ward nurses 272 Crtera Average value Crtera Average value Crtera Average value vs W 2 W 2 W 5 vs W 6 vs W 3 W 2 vs 0 W 5 vs W 7 vs W 4 W 3 vs W 4 W 5 vs W 5 W 3 vs W 5 W 5 vs W 6 W 3 vs W 6 W 5 vs 0 vs W 7 W 3 vs W 7 W 6 vs W 7 W 3 W 6 W 3 W 6 vs 0 W 3 vs 0 W 6 vs 0 W 2 vs W 3 W 4 vs W 5 W 7 W 2 vs W 4 W 4 vs W 6 W 7 W 2 vs W 5 W 4 vs W 7 W 7 vs 0 W 2 vs W 6 W 4 W 8 W 2 vs W 7 W 4 W 8 vs 0 W 2 W 4 vs 0 W 9 vs 0
Busness, Management and Educaton, 2013, 11(2): 256 280 Table 9. Parwse crtera comparson of ward physcans Crtera Average value Crtera Average value Crtera Average value vs W 2 W 2 W 5 vs W 6 vs W 3 W 2 vs 0 W 5 vs W 7 vs W 4 W 3 vs W 4 W 5 vs W 5 W 3 vs W 5 W 5 vs W 6 W 3 vs W 6 W 5 vs 0 vs W 7 W 3 vs W 7 W 6 vs W 7 W 3 W 6 W 3 W 6 vs 0 W 3 vs 0 W 6 vs 0 W 2 vs W 3 W 4 vs W 5 W 7 W 2 vs W 4 W 4 vs W 6 W 7 W 2 vs W 5 W 4 vs W 7 W 7 vs 0 W 2 vs W 6 W 4 W 8 W 2 vs W 7 W 4 W 8 vs 0 W 2 W 4 vs 0 W 9 vs 0 Usng the results of parwse comparson, the followng prorty matrxes wth justfable a j are derved: Table 10. Intal prorty matrx for evaluaton of crtera weghts of a ward nurse j w 1 w 2 w 3 w 4 w 5 w 6 w 7 w 8 w 9 w 10 a,j b P P w 1 1 1.404 1.404 1.404 1.404 1.404 1.404 1.404 1.404 1.404 13.6 135.59 0.1401 w 2 0.596 1.000 1.404 0.596 1.404 0.596 0.596 0.596 0.596 1.404 8.8 82.25 0.0850 w 3 0.596 0.429 1.000 0.596 0.596 0.596 1.404 0.596 0.596 1.404 7.8 76.31 0.0788 w 4 0.596 1.571 1.404 1.000 1.404 1.404 1.404 1.404 0.596 1.404 12.2 117.16 0.1210 w 5 0.596 0.429 1.571 0.429 1.000 0.596 0.596 0.596 0.596 0.596 7.0 66.85 0.0691 w 6 0.596 1.571 1.571 0.429 1.571 1.000 0.596 1.404 1.404 0.596 10.7 103.08 0.1065 w 7 0.596 1.571 0.429 0.429 1.571 1.571 1.000 1.404 0.596 0.596 9.8 94.77 0.0979 w 8 0.596 1.571 1.571 0.429 1.571 0.429 0.429 1.000 1.404 1.404 10.4 97.96 0.1012 w 9 0.596 1.571 1.571 1.571 1.571 0.429 1.571 0.429 1.000 1.404 11.7 112.34 0.1161 w 10 0.596 0.429 0.429 0.429 1.571 1.571 1.571 0.429 0.429 1 8.5 81.64 0.0843 Sum 967.96 1.0000 273
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton Table 11. Intal prorty matrx for evaluaton of crtera weghts of a ward physcan j w 1 w 2 w 3 w 4 w 5 w 6 w 7 w 8 w 9 w 10 a,jb P P w 1 1 1.571 1.571 1.571 1.571 1.571 1.571 1.571 1.571 1.571 15.1 147.74 0.1643 w 2 0.429 1 1.571 0.429 1.571 0.429 0.429 0.429 0.429 1.571 8.3 68.65 0.0764 w 3 0.429 0.329 1 0.429 0.429 0.429 0.429 0.429 0.429 1.571 5.9 52.98 0.0589 w 4 0.429 1.671 1.571 1 1.571 1.571 0.429 0.429 0.429 1.571 10.7 93.90 0.1044 w 5 0.429 0.329 1.671 0.329 1 0.429 0.429 0.429 0.429 0.429 5.9 51.55 0.0573 w 6 0.429 1.671 1.671 0.329 1.671 1 1.571 1.571 1.571 0.429 11.9 113.36 0.1261 w 7 0.429 1.671 1.671 1.671 1.671 0.329 1 0.429 0.429 1.571 10.9 93.65 0.1042 w 8 0.429 1.671 1.671 1.671 1.671 0.329 1.671 1 0.429 1.571 12.1 107.85 0.1200 w 9 0.429 1.671 1.671 1.671 1.671 0.329 1.671 0.329 1 1.571 12.0 106.59 0.1186 w 10 0.429 0.329 0.329 0.329 1.671 1.671 0.329 0.329 0.329 1 6.7 62.72 0.0698 Sum 898.99 1.0000 After the seres of prorty matrx perturbatons descrbed n PDM, K r estmaton error s mnmsed. Thus, when K f r Kr, z value s adjusted multplyng t by correcton coeffcent α teratvely. After the seres of ntal matrx transformatons, the followng resultng prorty matrxes are calculated: Table 12. Resultng prorty matrx for evaluaton of crtera weghts of a ward nurse j w 1 w 2 w 3 w 4 w 5 w 6 w 7 w 8 w 9 w 10 a,jb P P w 1 1 0.682 0.682 0.682 0.682 0.682 0.682 0.682 0.682 0.682 7.1 39.1 01389 w 2 0.289 1 0.682 0.289 0.682 0.289 0.289 0.289 0.289 0.682 4.8 24.1 0.0856 w 3 0.289 0.209 1 0.289 0.289 0.289 0.682 0.289 0.289 0.682 4.3 22.2 0.0788 w 4 0.289 0.763 0.682 1 0.682 0.682 0.682 0.682 0.289 0.682 6.4 34.0 0.1209 w 5 0.289 0.209 0.763 0.209 1 0.289 0.289 0.289 0.289 0.289 3.9 19.5 0.0695 w 6 0.289 0.763 0.763 0.209 0.763 1 0.289 0.682 0.682 0.289 5.7 29.9 0.1065 w 7 0.289 0.763 0.209 0.209 0.763 0.763 1 0.682 0.289 0.289 5.3 27.5 0.0978 w 8 0.289 0.763 0.763 0.209 0.763 0.209 0.209 1 0.682 0.682 5.6 28.6 0.1016 w 9 0.289 0.763 0.763 0.763 0.763 0.209 0.763 0.209 1 0.682 6.2 32.6 0.1160 w 10 0.289 0.209 0.209 0.209 0.763 0.763 0.763 0.209 0.209 1 4.6 23.7 0.0844 Sum 281.21 1.0000 274
Busness, Management and Educaton, 2013, 11(2): 256 280 Table 13. Resultng prorty matrx for evaluaton of crtera weghts of a ward physcan j w 1 w 2 w 3 w 4 w 5 w 6 w 7 w 8 w 9 w 10 a,jb P P w 1 1 5.590 5.590 5.590 5.590 5.590 5.590 5.590 5.590 5.590 51.3 1601.9 0.1662 w 2 1.528 1 5.590 1.528 5.590 1.528 1.528 1.528 1.528 5.590 26.9 725.0 0.0752 w 3 1.528 1.172 1 1.528 1.528 1.528 1.528 1.528 1.528 5.590 18.5 570.0 0.0591 w 4 1.528 5.946 5.590 1 5.590 5.590 1.528 1.528 1.528 5.590 35.4 1001.4 0.1039 w 5 1.528 1.172 5.946 1.172 1 1.528 1.528 1.528 1.528 1.528 18.5 551.8 0.0573 w 6 1.528 5.946 5.946 1.172 5.946 1 5.590 5.590 5.590 1.528 39.8 1225.3 0.1271 w 7 1.528 5.946 5.946 5.946 5.946 1.172 1 1.528 1.528 5.590 36.1 994.6 0.1032 w 8 1.528 5.946 5.946 5.946 5.946 1.172 5.946 1 1.528 5.590 40.5 1151.9 0.1195 w 9 1.528 5.946 5.946 5.946 5.946 1.172 5.946 1.172 1 5.590 40.2 1137.6 0.1180 w 10 1.528 1.172 1.172 1.172 5.946 5.946 1.172 1.172 1.172 1 21.5 678.0 0.0704 Sum 9637.67 1.0000 The normalsed weght P of each crteron s derved n the resultng matrces. When the crtera weghts are defned, the next step s to evaluate each employee of the same poston,.e. a nurse or physcan, by assgnng measured values for each crteron. Ths can be done n a number of ways. In terms of quanttatve ndcators, ths operaton s mathematcally trval. However, n terms of qualtatve crtera, dfferent approaches exst. The formal evaluaton s typcally easer for hosptals where routne HR processes are establshed and all employees undergo regularly scheduled performance apprasal meetngs. In other cases, t s suggested to use PDM to derve possbly more neutrally scored values of employee qualtatve features. The overall employee performance related value (PRV) calculaton s based on derved crtera weghts (Table 13) and measured or evaluated ndvdual employee ndcator values. The table used for ward nurses and physcans PRV calculaton s provded below. Table 14. Performance related value matrx for ward nurses and physcans Crtera rank weghts and employee performance values Crteron weght value P- j for nurses Crteron weght value P- j for physcans Crteron value of an ndvdual employee 0.14 0.09 0.08 0.12 0.07 0.11 0.10 0.10 0.12 0.08 0.17 0.08 0.06 0.10 0.06 0.13 0.10 0.12 0.12 0.07 p 1 p 2 p 3 p 4 p 5 p 6 p 7 p 8 p 9 p 10 275
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton The overall -th employee value for j-th crteron equals to: The employee performance-related value equals the sum of overall employee crteron values: j PRV p' P ', where -th - employee and j number of crtera (14) k k k 1 Applyng the calculated employee performance related value, the varable salary part s calculated as follows: Salaryvar, Salary fx. K PRV, (15) where Salary var, the varable part of the -th employee salary (performance-related pay); Salary fx, the fxed part of the -th employee salary. 6. Methods and tool sets for montorng PDM effcency The descrbed method for calculatng performance-related payment of medcal personnel s theoretcal and needs practcal approval. Therefore, t s essental to provde method and tools for evaluaton of the PDM mplementaton outcomes. The change of fnancal personnel ncentves may lead to a wde spectrum of mplcatons, whch n turn may nfluence organsaton actvtes not covered by the metrcs of the selected PDM ndcators. Hence, we propose the methodology for montorng and tmely dentfcaton of PDM use effects on an HPO operaton. The applcaton of statstcal analyss, pattern recognton, dmenson reducton and other data mnng methods allows to acqure more detaled nformaton at early stages. Data mnng can help determne f new patterns or assocatons come nto force and how they evolve after the ntroducton of a new employee remuneraton scheme. The followng systematc organsaton performance montorng and evaluaton approach s suggested: Actvty 1: Collect and analyse the change of each crteron K over tme (tme seres analyses) Actvty 2: Calculate the correlaton coeffcent to determne the nfluence of crteron weght to the measured values of PDM ndcators. Actvty 3: Perform the drect assocaton rules analyses,.e. generate rules on acqured PDM ndcator values and analyse the nterdependent rules. Actvty 4: Perform a comprehensve assocaton rules analyses,.e. generate rules on all avalable ndcators collected from an HPO medcal nformaton systems, e.g. HIS, EMR. The frst actvty s most basc and shows drect results of PDM applcaton. Dfferent vsualzaton methods wll be appled for perodc analyses of change n ndcators. Followng the used case example, two vsualzatons of the values of crtera set s w n 276
Busness, Management and Educaton, 2013, 11(2): 256 280 [w 1; w 10 ] changes over a perod of sx months are provded below. Fg. 3 llustrates normalsed measured crtera values. The normalsaton was performed by rescalng values to [0; 1] scale and applyng weght calculated by PDM. The mnmsed values mn c were adjusted to ts maxmsng values c. c 1,00 0,50 0,00 k10 k9 k8 k7 k6 k5 k4 k1 k3 k2 Fg. 3. The trend of PDM crtera values measured over sx months Fg. 4 represents the same trend applyng dmenson reducton. In ths example, elementary reductons to crtera value sum and mean values were performed. 1,2000 1,0000 0,8000 0,6000 0,4000 Sum Average 0,2000 0,0000 WT1 WT2 WT3 WT4 WT5 WT6 Fg. 4. The trend of descaled PDM crtera values over 6 months 277
J. Žaptorus. Applyng the prorty dstrbuton method for employee motvaton The next recommended step s to formally calculate correlaton R n (second actvty) of crteron K n weght and averaged measured ndcator value. Lnear regresson calculaton may be used, whch provdes statstcally well-defned evaluaton crtera. Hgher correlatons coupled wth hgher varance of measured ndcator values wll show hgher effect of the ndcator weght n the appled PDM model. Fnally, deeper analyses for hdden effects may be appled by usng assocaton rules learnng or nductve logc programmng methods. Identfed rules wth hgher confdence and smaller support values wll dentfy non-obvous rules wth hgher correctness of the rule. Dfferent exstng algorthms can be appled to fnd assocaton rules. Dependng on the qualty of the exstng data,.e. amount of mssng data and nosy data, approprate algorthms wll be appled. Accordng to multple researches, the best results are acheved by performng data pre-processng, proper parametersaton and applyng a set of dfferent DM algorthms (Dzemyda, Kurasova, Medvedev 2007; Špečkauskenė, Lukoševčus 2009). From the perspectve of a system engneerng, each organsaton s a complex system nterfacng wth other external systems. Therefore, the nformaton ganed n actvtes 2 4 should be consdered wth care, by nvolvng doman experts and analysng crtcally the causes of each change. 7. Conclusons Healthcare polcy makers and Healthcare Provder Organsatons are n a constant battle wth rsng healthcare expendture. There s a great need for nnovatve fnancal schemes, promotng greater effectveness of servces provded. A method utlzng mult-crtera decson support for the creaton of a performance-related remuneraton model n npatent healthcare facltes was created. The mplementaton of a well-balanced performance-related remuneraton model needs a systematc approach. Havng analysed the ssues of practcal mplementaton of performance-related pay schemes n the healthcare doman, a methodology consstng of performance ndcator selecton, use of the Prorty Dstrbuton Method and a method for montorng ts effcency s proposed. A parwse crtera comparson method called the Prorty Dstrbuton Method was used for weghted personnel performance crtera rankng. Defnng a personnel remuneraton model for a HPO s a complex and manfold task, whch hghly nfluences overall enterprse results. In order to determne ndvdual work outputs, healthcare provders have to use performance evaluaton models. Recent global changes n the healthcare doman have resulted n a new understandng that a complex set of quanttatve and qualtatve crtera should be appled for the overall provder s actvty evaluaton. When projectng ths perspectve to the evaluaton of ndvdual performance, the ssue arses regardng the qualtatve crtera relatve weght determnaton and ts nfluence on overall employee performance, expressed n weghted crteron rank. PDM was specfcally created to address these ssues and provde a practcally usable method, 278
Busness, Management and Educaton, 2013, 11(2): 256 280 n whch ndrectly measured qualtatve crtera are subjectvely evaluated by experts (Žaptorus 2006). Addtonally, the ssues of performance crtera selecton for PDM and evaluaton of PDM applcaton results were dscussed. A method for healthcare specfc crtera selecton conssts of sx steps. The method emphases the use of well-defned crtera n healthcare legslaton and healthcare sector best practces for settng the ntal ndcators. Specfc ndcators of an organsaton can be derved from ntal ones by way of applyng ntellgent data analyss technques to avalable provder statstcal, clncal and HR data. Use of assocaton rules learnng and other data mnng methods can reveal addtonal non-obvous ndcators, whch can be ncluded n PDM calculatons. To understand the appled PDM outcomes, the routne montorng and recurrng evaluaton of ndvdual and overall HPO performance s performed. The change of fnancal personnel ncentves may also lead to unpredctable mplcatons, whch could nfluence provder s actvtes not covered by ndcators selected for PDM. Therefore, four actvtes allowng drect and ndrect evaluaton of enterprse operaton have been proposed. Data vsualsaton and dmenson reducton technques are useful for regular montorng of crtera used n PDM. Crtera weght and measured crtera values change correlaton analyses may be used for a more formal evaluaton of weghted rank performance of the resultng crteron. Fnally, data mnng methods,.e. assocaton rules mnng, and nductve logc programmng may be used to dscover hdden patterns. Acknowledgements Ths research was funded by the Research Councl of Lthuana, the grant No. IEP- 01/2012of. References Abramson, P. R.; Inglehart, R. 1995. Value Change n Global Perspectve. Ana Arbor, Unversty of Mchgan Press. Bellazz, R.; Zupan, B. 2008. Predctve data mnng n clncal medcne: Current ssues and gudelnes, Internatonal Journal of Medcal Informatcs 77: 81 97. http://dx.do.org/10.1016/j.jmednf.2006.11.006 Berka, P.; Rauch, J.; Zghed, D. A. 2009. Data mnng and Medcal Knowledge Management Cases and Applcatons. Idea Group Inc (IGI). http://dx.do.org/10.4018/978-1-60566-218-3 Beshelev, S. D.; Gurvch, F. G. 1974. Matematko-statstcheske metody ekspertnykh otsenok. Moskva: Statstka (n Russan). Buchan, J.; Black, S. 2011. The mpact of pay ncreases on nurses labour market: a revew of evdence from four OECD countres, OECD Health Workng Paper 57 [nteractve]. Avalable from Internet: http://search.oecd. org/offcaldocuments/dsplaydocumentpdf/?cotedelsa/hea/wd/hwp(2011)4&doclanguageen Darves, B. 2011. Physcan Compensaton Models: Bg Changes Ahead, New England Journal of Medcne Career Centre [accessed on 20 Aprl 2013]. Avalable from Internet: http://www.nejmcareercenter.org/artcle/92/physcan-compensaton-models-bg-changes-ahead/ 279