abc ordenamiento 351.pdf

7/29/2019 ABC Ordenamiento 351.pdf

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351Am J Health -Syst Pharm Vol 57 Feb 15, 2000

PRIMERS Inventory

M odern inven tor y an alysis t echn iquesD AN N SALAMIE

DANN SALAMIE, C.P.A., M.S.I.E., is President, General Partner for Pharma-cy Management and Contr ol Ltd., P.O. Box 8639, Charleston, WV 25303([email protected]).

Mr. Salamie owns the copyright to the set of instructions and form ulasrequired for sort- based analysis (Sort AnalysisSM), formal use of the Pointof Diminishing Returns (PODRSM), generation of specific Exceptions Re-

portssm, and activity-based an alysis (Activity Analysissm). Th ese copyrightedinstructions form the basis of this article and are intended solely for theprivate use of readers.

Copyright 2000, American Society of Health-System Pharmacists,Inc. All rights reserved. 1079-2082/00/ 0202-0351$06.00.

Abstract: Modern t echniques for manag-

ing p harmacy invento ries are described.

Pharmacists should rely on modern

techniques, such as sort-based and activi-

ty-based analyses, for m anaging pharm a-cy invento ries, containing d rug costs, per-

f o r m ing r ep lacemen t - and - el im ina t i on

analysis, and monitoring the health sys-

tem s operations. Unit price and quant ity

are the two basic inventory-control ap-

proaches; however, modern techniques

recognize quantity as the more useful of

the t wo . The primary areas of the pharm a-

cys activities mu st be taken int o consider-

ation. Pharmacists mu st learn to divide in-

ventory analys is prob lems in to sets o f

smaller issues.

Mod ern invento ry analyses that take into

account annual quantity, unit price, totalannual cost, and the h ealth system s uniqu e

act ivi t ies provide the pharmacist with a

practical basis for invento ry managem ent.

Index terms: Administrat ion; Auto mation;

Inventory; Pharmacy, institu tional, hospital

Am J Health-Syst Pharm . 2000; 57:351-67

he management of pharmaceuti-cal inventory and supply posesmajor prob lems for the pharmacy

department. The pharmacy must en-

sure uninterrupted patient serviceswithout incurring the cost of main-taining every possible drug in the in-ventory. Some pharmacies receive4000 or m ore line items into inventoryduring a year. Since inventories are solarge, perpetual inventory systemsrarely are accurate. With the currenttrend of reducing the pharmacy de-partment staff, it is difficult to devotepersonnel time to inventory analysis.Nevertheless, inventory analysis is re-

quired for containing costs. Replacinghigh-cost drug products with lower-cost, yet therapeutically equivalent,ones is a desirable cost-saving mea-sure. Reducing the n um ber of items inthe inventory also reduces material-handling costs and perpetual invento-ry complexity. Most cost accountingand inventory systems can generate anannu al utilization repor t, but th ese re-ports are generally much too large toevaluate by hand. Therefore, it is usu-ally too tim e-consuming t o systemati-cally review an inventory to identifydrugs to replace or eliminate. It is de-sirable to have an automated systemfor man aging this problem.

This primer introduces the phar-macist to techniques for performing

T

replacement-and-elimination anal-

ysis. These techniques can be ap-plied to help fine-tun e perpetual in-ventory systems. Reducing the sizeand co st of an inventory is an essen-tial step before addr essing the pro b-lems of when and how much of anitem to purchase. Although thetechniques are intend ed to be auto-mated (with spreadsheet software,such as Lotus and M icrosoft Excel),this article focuses on the theoreti-cal and analytical bases of the auto-mated system. To emphasize thepractical application of these ap-proaches, this primer includes casestudies that represent two health-system pharmacy applications: anon profit medical center and a Vet-eran s Affairs (VA) hosp ital.

Since this primer is intended to

enable pharm acists to app roach real-life drug replacement-and-elimina-tion problems, statistical methodswill not em phasize hypothesis testingor other familiar statistics. Instead,the primer uses statistics devised tobe practical and effective in manag-ing the com plexity of inventory anal-ysis. The best strategy for managingthe com plexity of large inventories isto divide the inventor y problem intomanageable components. This ap-proach is best described as tearingoff the corner, as explained byMusashi.1 The sim ple math p resentedin this article is consistent with thisancient strategy.

This primer does not provide thereader with detailed keystroke-by-


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352 Am J Health -Syst Pharm Vol 57 Feb 15, 2000

PRIMERS Inventory

keystroke information on the use ofspreadsheet software. Instead, it fo-cuses on modern techniques for in-ventory analysis. The instructionsprovided in this article are explicit

enough that spreadsheet-proficientpharm acists can perform the tasks bythemselves or provide the directionsto o ther proficient spreadsheet users.

The inventory prob lem addressedin this primer focuses on the rela-tionship between the health-systempharmacy and i t s supp l iers andwholesalers. Quantities analyzed arethe quantities delivered at the healthsystems receiving d oor . Similar an al-ysis is recommended to determinethe relationship between the health-system pharmacy and its various in-ternal service points, including de-centralized pharmacies, inpatientcenters, outpatient centers, and i.v.preparation room s. The drugs evalu-ated include brand-name drugs andtheir generic equivalents as separateline items, since, although similar,these dru gs have different pu rchasingidentification nu mbers. Th e consoli-dation of brand-name and genericdrugs can be perform ed by som e pur-

chasing software packages, but notall. Therefore, consolidation issuesare not discussed.

Classic invent ory man agem enttheory

The fundamental theory for theapplication of the first technique,sort-based an alysis, was first pr esent-ed by nineteenth-century economistPareto, who demonstrated that 80%of the wealth in Italy was controlled

by 20% o f the popu lation. This workis the origin of the familiar 80/20rule. The idea that economic impor-tance is disproportionate with re-spect to its individual elements wasnew. Som e time later, the concept ofeconomic dispropor tion was appliedto inventory items and came to beknown as ABC inventory theo ry. Ac-cording to H otaling,2 ABC inventorytheory predicts that, on the average,70% of pharm acy purchase costs are

scribed by the following form ula: C=P Q , where C is the total annualpurchase cost (i.e., total economicforce), P is the unit price of the in-ventory line item , and Q is the annu al

unit volume of the inventory item.This formula is similar to the forceformula from physics stating thatforce is the product of mass timesacceleration.

The relationship of the economicformula to the physics formula willbecome more clear when the graphsare analyzed in the next section. Fornow, the econom ic force formu la canbe used to illustrate the difficultiesencountered when applying ABC in-ventory theory. For example, Hisma-nal (astemizole, Janssen) 10-mg tab-lets had been a C inventory item inthe VA hospital inventory, with aneconom ic force of $522.80 (5 un its $104.56/unit), and 1% Xylocaine(lidocaine hydrochloride, Astra) withepinephrine injection had likewisebeen a C inventor y item, with an eco-nomic force of $520 (400 units $1.30/unit). Although these two in-ventory line items have essentiallyequivalent economic forces, they

have greatly different prices and unitvolumes. If the definition for C lineitems used by Hotaling2 is applied,the looser con tro l and reducedrecord keeping could result in a largefinancial mistake in the pur chasing ofHismanal. Clearly, much more in-ventor y control and record keeping isrequired for Hismanal than for theXylocaine product. ABC inventorytheory fails to distinguish betweenproducts that have vastly different

prices (mass) and quant ities (acceler-ation) while having the same relativetotal ann ual costs (econom ic force).

Similar problems can also be d em-onstrated in the A inventory items.Eulexin (flutamide, Schering) 125-mg capsules had an economic forceof $40,877.46 (162 units $252.33/unit), and albuterol m etered-dose in-haler had an economic force of$40,318.60 (18,580 units $2.17/unit). Although these products had

for 10% of the items (A items), 20%for 20% of the items (B items), and10% for 70% of the items (C items).H owever, there is a great deal of vari-ance among the percent divisions

noted by various author s. For exam-ple, Berger3 stated that 80% of thepurchase costs account for 20% ofthe inventory items, 15% o f the pur-chase costs account for 15% of theitems, and 5% of the purchase costsaccount for the rem aining 65% of theitems. Operations management text-books are not any m ore precise thanthe guidelines provided in the phar-macy literature. According to Heizerand Rende,4 70% to 80% of the pur-chase costs represent 15% of the in-ventory items, 15% to 25% of thepurchase costs represent 30% of theitems, and 5% of the purchase costsrepresent the remaining 55%. De-spite the wide variance in the cutoffpoints recommended by various au-thors, the fundamental concept isclear: Focus management resourceson the few critical inventory itemsand not on the many trivial items.5

The m anagement effort an d financialresources required to monitor im-

portant items cannot be justified forall items.

According to Ho taling,2 The ob-ject ive in determ in ing th ese cat ego-ries is to devote the maximum timeand monitoring to the A items thatrepresent the greatest portion of ex-pen ditu re. Since C items are r elative-ly insignificant in expenditure, theywarrant looser control resulting inless record keeping, lower turnover,higher safety stock, and infrequent

number of orders. The B items aregiven intermediate at tention andcontrol.

The pr oblem with ABC inventoryanalysis is that it characterizes eachitem in the inventory only by the dol-lar amou nt o f its total annu al cost, ormore simply, total cost. Total cost isthe un it price multiplied by the totalannual quantity purchased for anygiven line item . The total ann ual costis a measure of economic force de-


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PRIMERS Inventory

the same relative total annual costs,there was more than a 100-fold dif-ference in their u nit volum es. Since Aitems require maximum time andmonitoring efforts, the ultra-high

volume of albuterol could have rep-resented an inordinate expenditurefor inventory control. A mistake,such as ordering too mu ch albuterol,would have had very little economicconsequence. The high demand com -bined with th e low unit value wouldhave minimized the economic im-pact of a mistake. The cost of apply-ing strong inventory control to thisproduct would be a greater burdenthan the cost of overpurchasing.

Sort-based analysis is specificallydesigned to overcome th e aforemen-tion ed deficiencies of ABC invent orytheory.

The log ic of sort-based ana lysis

Sort-based analysis takes into ac-count the entire economic forceequation by contrasting the unit p rice,the annual quantity, and the total an-nu al cost. By analyzing the entire eco-nomic force function, sort-based anal-ysis provides a more robust model

than ABC inventory theory.Sort-based analysis begins with

the application of the fundamentalelements of ABC inventory. As withABC inventory, the first step in sort-based analysis is to create a list of alldrug and support items used by thepharmacy. The inventory item num-ber (usually used in purchasing)should be included, along with a de-scription of the d rug and its total an-nual dollar purchases. Unlike ABC

inventory analysis, sort-based analy-sis also requires total ann ual un it vol-ume and the unit price for the in-ventory line item. Together, the unitprice, the total annual quantity, andthe total ann ual cost are referred to asthe inventory param eters. A simplifiedlayout of inventory data, with only 43line items, is shown in Figure 1.

The second step is to sort th e datain descending order o f total econom -ic force (i.e., total annual cost). Sort

annual cost of all inventory lineitems.

If this were ABC inventory analy-sis, we would simply look down thecolum n showing cum ulative percent-

ages of total cost and find a suitablemaximu m for the A items. For exam-ple, line item 9, lithium carbonate300 mg, would represent the last Aitem; the A items would represent75% of the annual purchases and21% of the total line items of the in-ventory. Similarly, line item 26,thioridazine hydrochloride 25 mg,would represent the end of the Bitems. The B items would representthe n ext 39% of line items (60% m i-nus 21%), for an additional annualtotal cost of 14% of annu al purchases(95% minus 81%). By default, lineitem 43, glycerin adult suppository,would be th e last C invento ry item. Cinventor y items would r epresent 40%of the total inventory line items(100% minus 60%) and 5% of thecumulative total annual cost (100%minus 95%).

In sort- based an alysis, the com pu-tations are extended to include thecumu lative percentage of total quan -

tity and th e cum ulative percentage ofunit price. These calculations areused to d isplay graphs of the invento-ry parameters to aid in the interpre-tation of the data.

The cum ulative percentage of totalquantity is calculated from the fol-lowing equ ation:

Cum ulative % total quantityi

= cum ulative % total quantityi1

+ total quantityi/ total quan tities

where cumu lative % total quantityi isthe cumulative percentage of totalquantity achieved by the ith invento-ry line item, cumulative % totalquantity

i1is the cum ulative percent-

age of total quantity achieved by theprevious inventory line item, and total quantities is the sum of totalquan tities for all inventory line items.The cumulative percentage of totalquantity (Figure 1) is calculated thesame way as the cumulative percent-

the inventory data as follows: prima-ry sort, total annu al cost in descend-ing order; secondary sort, total annu -al quantity in d escending order; andtertiary sort, u nit p rice in descending

order. After the inventory line itemsare sorted from highest total annualcost to lowest total cost, the total forall 43 line items is provided at thebottom of those three colum ns.

Next, calculate the cumulativepercentage of line items (leftmostcolum n in Figure 1) as follows:

Cum ulative % line itemi=

(cumulative line itemi1

+ 1/n ) 100

where cumulative % line itemiis the

cumulative percentage of line items

achieved by the ith inventory lineitem , cum ulative line item

i1is the cu-

mulative line items achieved by theprevious inventory line item, and n isthe total number of line items. Thecumulative percentage of line itemsfor th e last line item is 100%.

In the calculation of the cumula-tive percentage for each line item,and for each inventory parameter,the denominator is the summationfor each parameter. For example,

each drugs total cost is divided bythe total cost summation in order toget the d rugs percent contribution tothe total. In sequence, each line-itempercentage of total cost is calculatedand then added to the previous lineitems cumulative percentage. In thisway, when the p ercent contribution ofthe last invento ry line item is calculat-ed and add ed to the previous cum ula-tive total, 100% of the cum ulative totalcost is achieved. The equation for cre-ating the percentages of the total is asfollows:

Cum ulative % total costi

= cumu lative % total costi1

+ total costi/ total costs

where cum ulative % total costiis the

cumulative percentage of total costachieved by the ith inventory lineitem, cum ulative % total cost

i1is the

cumulative percentage of total costachieved by the previous inventoryline item, an d tota l costs is the tot al


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PRIMERS Inventory

Figure 1. Layout of inv entory d ata for sort-based analysis. This layout w as achieved w ith spreadsheet software. The p roduct descriptio ns include t he

abbreviations used in the o riginal records.

16.921.422.925.129.930.932.435.838.343.844.646.253.056.657.2

59.063.467.970.972.077.579.280.681.183.385.187.388.990.091.292.792.893.293.794.294.995.096.197.398.699.399.9

100.0

2.612.126.631.333.141.647.249.151.652.760.062.663.163.967.8

69.069.469.870.471.872.173.074.076.977.478.178.679.280.2

80.981.590.091.893.294.494.997.898.198.398.598.899.0

100.0

21.041.751.956.961.165.269.172.375.378.380.982.984.585.987.1

88.189.089.990.791.492.292.993.694.294.895.395.896.396.8

97.397.798.198.498.799.099.299.499.599.699.899.999.9

100.0

7,2357,1533,5101,7281,4411,4031,3731,0851,0501,029

884700550480405

342326302274265258254228205199183182176174

154138134119107101

5756525049292420

34,483802

64236360115

45210138

486228

18064122097

2911101436

72224731316121724

1814210

4435301272

76666

24

2,47758

113.0430.31

9.7515.0332.03

6.689.95

22.6016.9436.75

4.9110.9345.8023.98

4.18

11.7929.6130.2119.59

7.3736.8011.55

9.522.81

15.3311.4215.2010.35

7.23

8.549.880.642.703.073.364.710.787.388.358.224.773.980.82

668.8615.55

SUCRALFATE 1GM TTRIAMTERENE/HCTZ 37.5/25 GTHEOPHYLLINE 300MG $ASODIUM POLY SULF 15GM/ 60M L RINTRON A 5 M IL IUMYCELEX 1%FLUOCINONIDE .05% $TPROPULSID 10MGLITHIUM CARBONATE 300M G $RHC HOLL 3274 POUCH DRAIN BXAMITRIPTYLINE HCL 25MG GHC CONV 25641 POUC DRN 10X10LEVOPHED BIT .1% AM PUL L6HC HOLL 3184 STOMA CAP BX30CLOTRIMAZOLE CRM 1% OTC $T

DELTASONE 20MGCAPTOPRIL 50MG BMORPHINE 25M G/M L 10ML MRETIN-A 0.1%BUMETANIDE 0.5M G $MLANOXIN 0.25MG/ML 2MLINDOMETHACIN 2 5MG $ZHEPARIN 10M U/M L 1M L SDVSEBEX SHAM POO 4OZDIFLUNISAL 250M G RTHIORIDAZINE HCL 25M GHC CONV 22567 WAFER BX5 DURHSUCCINYLCHOLINE 20MG/ML 10MLALBUTEROL .083% 3ML R

MUCOSIL 10% 10M L DCERUMENEXSOLU-CORTEF 100 MG AOV/ DILTUBERCULIN PPD 5TU 10 TESTALPRAZOLAM 1MG GJJ NU GAUZE IODO 1/ 2X5 87LOXITANE 25MGQ-TUSSIN D M (UNBXD) QCYPROHEPTADINE HCL 4MG ZVITAMIN D 50000U UDOXEPIN 10MG/ML ORAL WCHLORDIAZEPOXIDE 5MG RUGXANAX .5MGGLYCERIN ADULT G

TOTALPoint of diminishing returns

123456789

101112131415

1617181920212223242526272829

3031323334353637383940414243

2579

1214161921232628303335

3740424447495153565860636567

70727477798184868891939598

100

CUMULATIVE% UNITPRICE

CUMULATIVE% TOTAL

QUANTITY

CUMULATIVE% TOTAL

COSTTOTAL

COST ($)TOTAL

QUANTITY

LAST UNITPRICE ($)DESCRIPTIONINDEX

%LINE

ITEMS

age of total cost, but the sum of theun it volume for each line item is usedas the denominator , and the un it vol-umes for each line item are the nu-merator s in sequence.

The same computation is madefor unit pr ices, with the tot al sum ofthe individual unit prices used as the

denominator and the unit price ofeach line item handled in the samemanner as in the other two columns.The equ ation is as follows:

Cum ulative % un it pricei

= cum ulative % un it pricei1

+ unit pricei/ unit prices

where cumulative % unit pricei

is thecumulative percentage of unit priceachieved by the ith inventor y line item,cumu lative % un it price

i1is the cumu -

lative percentage of unit price achievedby the previous inventory line item,and unit prices is the sum of unitprices for all inventory line item s.


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PRIMERS Inventory

The last computation in sort-based analysis is to calculate the po intof diminishing returns (PODR). ThePODR is the total of the unit prices,total qu ant ities, or to tal costs divided

by the number of line items. ThePODR for each inventory parameteris as follows:

PODRtotal cost

= total costs/n

PODRtotal quantity

= total quantities/n

PODRunit price

= un it prices/n

The reader m ay have noticed that cal-culating the PO DR is the same as cal-culating the average unit price, aver-age quantity, and average total cost.Although this is true, the term aver-age is avoided in sor t-b ased analysisbecause average is a statistical m ea-sure. Sort-based analysis does notrely on statistical methods and doesnot include means and standard de-viations. Average would be mis-leading and confusing in the cont extof this primer.

Before the PODR can be used, thedata in Figure 1 must be graphed.The cumulative percent line itemsmu st be used as thex-axis. The graph

should be a line or scatter graph,without symbols for each d ata point.The use of symbols for each datapoint results in a graph that is clut-tered and that takes too much tim e tocreate and print. Omitting the sym-bols for each data point also high-lights the difference between smoothcurves and curves with wavy pat-terns. Once the x-axis and t he graphtype are selected, the individualcurves can be added. The cumulative

percentages for total cost, total quan-tity, and u nit price are included in thegraphs. Make sure that th ey-axis andth e x-axis terminate at exactly 100%.The length of the axes should be ad-justed so th at a perfect ly square graphis created. In t his way, the grap h willshow a directly proportional slope(changes along the y-axis directlycomparable to changes along the x-axis) on the screen and on a prin tout.For example, a 1% rise in total cost

t ive percentage of to tal quanti ty(blue) and cumulative percentage ofunit price (green) are wavy and donot have the same r apid accelerationin the first 10% t o 20% of the x-axis.

This is because the primary sort wasnot for cum ulative percentage of unitprices or cumulative percentage oftotal quan tity.

The head of the curve and th e tailof the curve are important in sort-based analysis. The head o f the curveis the rapidly accelerating area in thefirst 10% to 20% of the x-axis, repre-senting the first 1020% cumulativepercentage of line items. Since thedata were sorted in d escending order,the beginn ing items are the on es withthe largest economic force. There-fore, the cumulative percent valuesare disproportionately greater thanfor those on t he tail of the curve. Theresult appears as a rapidly accelerat-ing segment of the curve on thegraph. Th e tail of the curve is the flat

would have a distance equal to a 1%increase in line items.

Th ex-axis shou ld be labeled per -centage of all inventory line items.Th e y-axis should be labeled per-

centage of cumulative inventory pa-ram eters (or percentage of cum ula-tive quantity, unit price, and totalcost). Designate which curve corre-sponds to which parameter. It ishelpful to color code the curves andto ad d grid lines. Because the graph issquare, th e grid lines shou ld be at theexact same percentages for each axis(e.g., 10% horizontal and 10% verti-cal, resulting in grid squares repre-sen t ing 10% increments on thegraph).

Figure 2 shows a graph o f the datafrom Figure 1. Note the smoothnessof the curve for cum ulative percent-age of total cost (red). It is smoothbecause the p rimary sort was for cu-m ulative percentage of tot al cost. No-tice also that the curves for cumula-

Figure 2. Inventory line item s with prim ary sort by cum ulative percentage of tot al cost, in descend-ing ord er. PODR = po int of d imin ishing returns.

100

80

60

40

20

0

0 20 40 60 80 100

%C

umulative

InventoryParameters

% All Inventory Line Items

+ PODR

Quantity

Unit price

Total cost


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PRIMERS Inventory

region of the curve that accounts forthe last 50% or so of th e cum ulativepercentage of line items. The exactpoint where the head of the curveends an d th e tail of the cur ve begins is

the PODR. Graphing the PODR isrelevant o nly for th e curve represent-ing the cumu lative percent param eterthat was selected as the primarysortin this case, the cumulativepercent age of total cost. The PODR ismuch more dramatic in real-worldinventories.

In the last line of Figure 1, we seethat the PODR for the total cost is$802. Searchin g line it em by line itemthrough the total cost column, wefind th at the last amo unt greater than$802 is $884. This amount corre-sponds to line item 11, amitriptylinehydrochloride 25 mg. Reading acrossthe line for amitr iptyline, we find th atthe POD R represents 81% of the cu-mulative percentage of total cost for26% of the cumulative percentage oftotal line items. Thu s, 26% of the lineitems result in 81% of the total cost(81/26). We can emp irically calculatethe exact econom ic dispropo rtion forany given inventory param eter by us-

ing so r t -based analys is and thePOD R. In Figure 2, the POD R is indi-cated by the addition sign on t he cu-mulative percentage of total costcurve.

Berger 6 identified unit price andquantity as the two basic inventorycontrol approaches and concludedthat qu antity contr ol is the m ore use-ful of the two. Sort-based analysisalso em phasizes quantity as the m oreuseful basis for inventory control.

The following example may help thereader understand why both Bergerand sort-based analysis emphasizethe management of total purchasingcost through a focus on quant ities.

Imagine that you are at a restau-rant and order a $15 bottle of wine.The waiter goes to the bart ender, ob-tains the bottle, opens it, and servesyou and your date. The gratuityearned by the waiter for this effort is$3 ($15 20%). Now imagine that

its acceleration in the initial percent-ages of line items is much greaterthan that of the other two curves.Also note t hat t he shape of the cur vefor cumulative percentage of total

cost m ost closely resem bles the curvefor the cum ulative percentage of totalquantity. Because the graph repre-sents the inventory line items in de-scending order of total quantity, thesimilar shape of the curve for cum u-lative percentage of total cost indi-cates that the order of total cost isalso very close to descending order.a

Figure 3 shows this close relationshipbetween to tal cost and total quant ity.This relationship is much more dra-matic for r eal-world inventories andcan be viewed even when th e prim arysort is by cumulative percentage oftotal cost.

The curves for cumulative per-centage of total cost and unit pricehave a wavy pattern. A wavy patternis always exhibited for the two inven-tory param eters that are n ot selectedas the primary sort. When the entireinventory data set is sorted by usingquant ity as the prim ary sort, th e wavypattern of the curve for cumulative

percentage of total cost is of particu-lar importan ce. The impo rtance is inbreaking out and setting aside someof the inventory items in the excep-tion reports, which are extremelyuseful in real-world applications ofsort-based analysis but are not veryrelevant in th is simp lified example.

The fundamentals of sort-basedanalysis are not very complicated.Certainly, the mathematics are sim-ple enough. Yet, this simple concept

forms the basis of a comprehensivemeth od for analyzing inventory.

App lication o f sort-b ased analysis

Generation of initial inventory

report. To begin a sort- based analysisof an inventory of pharmaceuticalsupp lies, the first step is to ob tain theinventory data from the informationsystems department. However, thedata are rarely sortab le with a spread-sheet program. In fact, pharmacists

the couple next to you or ders a bottleof expensive champagne from thesame waiter. Since the champagnecosts $150, the waiter earn s a gratu ityof $30 ($150 20%), even though

the amount of activity performed bythe waiter is the same as that for thewine. Basing the gratuity on the dol-lar value of the p urchase is not a real-istic measure of the work activity per-formed. The control on the cham-pagne was greater than the contro l onthe wine before t he waiters service.

In a health-system pharmacy set-ting, pharmacy management is con-cerned with managing activity. Theactivity is more closely associatedwith the amount of material beinghand led, that is, the quan tity of phar-m aceutical inventor y. The quan titieshand led d etermine t he pace of activi-ty in the inventory management op-eration of the ph arm acy. In m ost cas-es, the dollar value of the item han-dled is not the determ ining factor inthe amount of activity. The dollarvalue determines the type of controlbefore work.

To further illustrate why bothBerger and sort-based analysis em-

phasize the m anagement of total pur-chasing cost by focusing on quanti-ties, re-sort the data from Figure 1first by total quantity (the primarysort) and second by total cost, both indescending order. (As a practicalnote, do not include the column s forcumulative percent or the summa-tions of the inventory parameter inthe sort ranges. Sorting these spread-sheet components can destroy theformu las within the sum m ations and

the percentages. Since sorting is fre-quently performed in sort-basedanalysis [hence the name], this rulemust always be followed.) Once thedatabase is re-sorted and th e cumu la-tive percentage columns have beenrecalculated, regenerate the graph.Figure 3 shows a graph of the datafrom Figure 1 with total quantity asthe p r imary so r t . Note that thesmooth curve is now the one for cu-m ulative percent age of quant ities and


7/17


PRIMERS Inventory

full report is 15,053 lines long). No-tice that the total quan tity of any par-ticular line item is not provided inthis report. Instead, monthly pur-chase quantities are provided. Also

notice that the price per unit is not onthe same line as the item name andmonthly quantity data. Therefore,this report m ust be processed furtherto sum the mo nth ly pur chase quanti-ties into a single annual purchasequantity and to move the unit priceonto the same line as the quantitydata. To accom plish this data m anip-ulation , it is often n ecessary to obtainadditional assistance from the infor-mation systems department. Thepharmacist should ask to receive thisreport electronically instead of as ahard copy. Once the report is in anASCII format file, the informationsystems department can pr ogram thedata man ipulations required to parsethe data into suitable cells in thespreadsheet. Then the pharmacy de-partment can run the program atwill. The drug inventory resultingfrom the parsing and sorting of thehistorical repor t is called the am assedinventory.

Table 1 contains inventory infor-mation for a medical center and a VAhospital. The first line of the tablerepresents the num ber of lines of datain the original inventory history re-port obtained directly from the pur-chasing system. After the data areparsed into cells and the drug infor-mation is consolidated on a singleline, the number of actual drug line

Figure 3. Inventory line items with primary sort by total quantity, in descending order. PODR =point of dim inishing returns.

100

80

60

40

20

0

%C

umulativeInventoryParame

ters

0 20 40 60 80 100

% of All Inventory Line Items

+ PODR

Figure 4. Samp le inventory h istory report. The blank lines (not shown ) and mu ltiple lines for each item are features of the actual report .

TTLDECNOVOCTSEPAUGJULJUNMAYAPRMARFEBJANSU SIZEDESCRIPTION

&K0S (S7BJAN 5,199 9 2 LINE USAGE REPORT BY BRAND NAM E PAGE: 1

(s20H ITEM#

20/20 EYE DROP

8 MOP

A AND D M ED OINT

(S7B0218099 (S0B

NDC# 12258021505 PURCHASES LAST 12 MO $31.32 LAST PRICE 1.74

USER#(S7B0406363 (S0B

NDC# 00187065142 PURCHASES LAST 12 M O $822.36 LAST PRICE 137.06

USER#(S7B0263210 (S0B

NDC# 00085141002 PURCHASES LAST 12 MO $18.66 LAST PRICE 3.11

USER#

Quantity

Unit priceTotal cost

.5oz 0 0 0 0 0 0 0 6 6 18

50CP 0 0 0 2 0 0 2 0 6

4oz 4 0 0 0 0 0 2 0 0 4 0 0 6

are often faced with information-sys-tem reporting options that are notefficiently organized for data analy-

sis. To illustrate this problem, a sam-ple page from an inventory historyreport is provided in Figure 4 (the


8/17


PRIMERS Inventory

Table 1.

Sum m ary of Inven tories at a Veterans Affairs Hospital and aM edical Center

10,3604,040

39.0

04,040

110 (3)

716 (18)

0 (0)3,214

146,8964,387,385

1,3654646

0 (0)

0 (0)0 (0)

117 (4)

28,860 (20)

967,333 (22)

15,0532,752

18.3

5342,218

35 (2)

103 (5)

305 (14)1,775

355,9917,385,191

4,16120145

427 (24)

124,727 (35)697,991 (9)

102 (6)

4,659 (1)

278,933 (4)

No. of lines of data in 1998 purchasing rep ortNo. of lines of actual drug d ata in purchasing rep ortEfficiency of p urchasing report, %Sort analysis of inventory

No. of line item s wit h no inv entory activity in 1998(exception repo rt 1)

No. of line item s wit h invent ory activity in 1998No. (%) of line items with quant ity of 0 or less

(exception repo rt 2)No. (%) of line items with quant ity of 1 (except ion

report 3)No. (%) of line items wit h qu antity of 24 (exceptio n

report 4)Total no. of l ine items in active invent ory

Total quantity of d rugs and pharm aceutical supp liesin active invent ory

Total cost ($) of item s in active invent oryPoint of diminishing returns

Total cost ($)Quanti tyUnit p rice ($)

Activity analysis of invent oryNo. (%) of line items used for ou tpatient s onlyQuantity (%) of drug s and p harmaceutical supp lies

used for out patients onlyTotal cost ($, %) of item s used for o utp atients onlyNo. (%) of line item s used for in patient s onlyQuantity (%) of drug s and p harmaceutical supp lies

used for inpatients only

Total cost ($, %) of items used for in patients on ly

Variable

VeteransAffairs

HospitalMedicalCenter

items is only 2752. Therefore, theoriginal report generated by the VAhospitals information system wasonly 18% efficient. The same reportfor the medical center was only 39%efficient. These reports are seldomused in their printed form. In fact,neither hospital had ever used thesereports other than for sort-based

analysis.E x c e p t i o n r e p o r t s . O n ce th e

amassed inventor y has been obtainedand th e colum ns for cumulative per-cent are computed and organized asshown in Figure 1, the exception re-ports can be generated. The excep-tion r eports are d esigned to tear offspecific inventory line items andgroup them into four reports, eachwith its own informative attributes.Therefore, sort-based analysis iso-

lates the few line items that requirespecial management from the manythat do not require management. Theattributes of the four exception re-ports are sum m arized in Table 1.

The line item s in an y given excep-tion report are intended to be re-viewed thoroughly by the health carefacilitys pharmacists. Many impor-

tant aspects of the facilitys opera-tions and t rends can be learned. Mostimportant, any exception report willhave several line items that must bereturn ed to th e active inventory dataset for one reason or another. Theseshould be retu rned only after all oth-er exception reports are generated.After all of the exception reports aregenerated, the inventory items re-m aining in th e data set are referred toas the active inventory.

Exception report 1. Exception re-port 1 lists the line items that h ad n oactivity for the year under review. Ifthe line item was not u sed during theyear, chances are that there is no val-

ue listed for its unit price, quantityused, or an nual to tal cost. By m ovingthe cur sor to th e very last line item inthe spreadsheet, we can inspect thecolum n for unit pr ice, annual quanti-ty, or total annual cost. If these col-umns are blank, then simply movethe cursor up until you find entrieswith values. Once entries are foundin th ese colum ns, it is simple to insertrows to separate the blank line itemsfrom those that contain data. Thoseline items are listed in exception re-port 1. For the VA hospital, therewere 534 such items. There were nosuch item s for th e medical center. Ex-ception report 1 should be reviewedby a pharmacist for trends, errors,and other insights into the healthcare facilitys activities. Figure 5shows the first page of exception re-por t 1 for the VA hospit al.

Exception report 2. Once exceptionreport 1 has been prepared, excep-tion report 2 can be developed. Ex-

ception report 2 lists the line itemsthat have a quantity of zero or less.To obtain t his list, sort the rem aininginventory with total quantity as theprim ary sort in descending order. Forthe secondary sort, use the total an-nual cost in descending order. Onceagain, evaluate the bottom lines ofthe spreadsheet and work your wayup . The very last lines may even con-tain negative numbers for the threeinventory parameters. When you

find the last line item with the quan -tity of zero, insert rows at this point.The line items with quantities lessthan or equal to zero are now sepa-rated from the rest of the data set andare listed as exception repor t 2. FromTable 1, exception report 2 had 35line items for the VA hospital and110 line items for the medical center.On ce exception repor t 2 is generated,it is generally advisable to determinethe reasons for the zero an d n egative


9/17


PRIMERS Inventory

tity equal to 1 are now separatedfrom the rest of the data set and arelisted as exception r epor t 3. From Ta-ble 1, exception repor t 3 had 103 lineitems for the VA hospital and 716

line items for the m edical center . Fig-ure 7 is the first page of exceptionrepor t 3 for the VA hospital.

There ar e several reasons for sepa-rately evaluating the line items withquant ity equal to 1. First, the nu m berof line items in the data set (n ) is thedenominato r fo r ca lcu la t ing thePODR. By including the items withquant ity of 1, the denom inator is ex-aggerated. This exaggeration resultsin a deceptively lower PODR than ispract ical. Second , the list of line itemswith quant ity equal to 1 h as a practi-cal use as a managerial diagnostictool. Perhap s the item is a rarely useddrug that must be maintained in in-ventory. In that case, the item maysimply have expired and have beenreplaced to maintain the appropriatelevel of preparedness for the healthsystem. Conversely, the quantityequal to 1 may represent a very largenumber of unit doses. In either ofthese cases, the line item should be

returned to the active inventory. Onthe other hand, perhaps a particulardrug listed in exception report 3 hasan acceptable therapeutic alternativefor which a larger quantity is alreadybeing ordered. In this case, it can beargued that the pharm acy should notbe burdened with ordering a produ ctfor which an adequate alternative isavailable. Also, completely inappro-priate purchases have been isolatedin exception report 3. For example, a

h a i rb ru sh an d n o n p resc r ip t io nshampoo produ ct were discovered inthe list of line items with quantityequal to 1. Further investigation bypharm acy m anagement revealed thatemployees were overstepping theirprivileges by using pharmacy pur-chasing for their personal conve-nience.

Exception report 4. Exception re-por t 4 is a little more comp licated thanthe first three. (Readers are reminded

Figure 5. Exception report 1, page 1 drugs not purchased.

ACCUSURE SYRINGE .5ML 28GACEBUTOLOL HCL 200M GACETA GESIC

ACETAMINOPHEN 325MGACETAMINOPHEN/COD 12.5MLACULAR .5%ACYCLOVIR 200MGADVERA LIQUID CHOCOLATE 6X8OZAK-DILATE OPHTH 1 0%AK-NACL 5% OPHTHAK-TROL OPHTHAK-TROL OPHTHALBUTEROL TAB 4MG 500ALLOPURINOL 100MGALOM IDE OPHTH .1%ALUMINUM HYD GEL 320MG/5M LAMANTADINE 100MGAMIKIN IM/ IV 500M G 2ML

AMITRIPTYLINE HCL 10MGAMITRIPTYLINE HCL 25MGAMITRIPTYLINE HCL 25MGAM ITRPTLN TAB 25M G 1000AM ITRPTLN TAB 50M G 1000AMPICILLIN 250MGAM PICILLIN INJ 1GM 1 M LANA KIT ANAPHYLAXIS TRTMNTANAFRANIL 25MGANAFRANIL 50MGANDROID 10ANTIPYRINE/BENZO CAINE OTICANTIVENIN POLYVALENT COMBO D/ SANUSERTANUSERT SUPP 24ARISTOCORT LP 0.025%ARMOUR THYROID 1GR (60MG)ART TEARS SOL STRL 15M LARTIFICIAL TEARS LUBRICANTASPIRIN 6 00M GASPIRIN 81MG CHEWABLEATENOLOL 100MGATENOLOL 50MGATROHIST PLUSATROPINE 1MG/ML 1MLATROPINE SULF 1% OPHTHAURALGAN OTIC W/DROPPERAVITENE WEB NON WOVN 35MMX35MMBACTERIOSTATIC 50M G/M L 3 0M L

BAGS A26 2 MIL 6X8BAGS A28 2 MIL 8X8BAGS BUBBLE PCHS 8X11.5

42259242234

500009

646562947275137372726505323675393389776088296251296269248773618322328989583336207423726174

87072587074192410050974550971195173129312655737177961177960344847243476185815962140962141744969429033

50935629567510325987271313361115575414808094664067757530361

631291917997

679506679472522151

123

456789

101112131415161718

1920212223242526272829303132333435363738394041424344454647

484950

DescriptionItem #Line Num ber

quantities reportedflaws in inter-nal control over the return of drugs,flaws in accoun ting, and ot her p roce-dural flaws can often be discovered.Further analysis may even revealcredits not received from wholesal-ers. Figure 6 shows exception report2 for th e VA hospital.

Exception report 3. Exception re-port 3 lists those item s with a quant i-ty equal to 1. Since the data set wassorted in descending order o f annualquan tity, it is simple to follow the lineitems up t he list un til the first quanti-ty equal to 2 is found. Insert rows atthis point. The line item s with qu an-


10/17


PRIMERS Inventory

Figure 6. Exception repo rt 2 invento ry items with a tot al quantity of zero or less.

(22.31)0.00

0.00(29.07)(60.76)

0.00(140.28)

(51.83)(12.00)

(5.46)(17.60)

0.00(160.20)

(31.98)(6.90)

(1,017.36)(22.50)

0.000.00

(60.12)(84.64)

(123.66)(48.96)

0.00(25.20)(45.42)

0.00(75.84)

(564.75)0.00

(114.10)(235.55)

(3.77)0.000.00

22.310.00

38.6029.0715.19

0.0070.1451.83

1.005.46

17.600.00

13.3515.99

3.4518.84

2.25

13.4217.9820.04

5.2920.6124.48

0.004.20

22.7176.00

6.3237.65

0.0022.8247.11

3.770.003.50

112

014121

12112

1222

5410

00

316

62162

01215

155

11

0

ANTABUSE 500M GANUSOL HC 25MG

AQUASOL A 25M UARTANE 2M GASENDIN 25MGBAC/ZINC/POLY B SULFCARBAMA ZEPINE 200M GCARDURA 1M GDEXACIDIN OPHTHDIETHYLSTIL TAB 1MG 100EPIFRIN 1%FELBATOL 400M GFLUOCINONID E .05%ISONIAZID 100M GISONIAZID 100M GISOPTO CARBACHOL OPHTH 1 .5%JJ BAND-A ID FLEXIBLE KNCK/FN

KERR 908 PLASTIC OINT JAR 8OKERR 916 PLASTIC OINT JAR 16M EXILETINE 150M GMURO 128 5% OPHTHMYLERAN 2MGNARDIL 15M GNAVANE 20M GNUPERCAINALPERPHENAZINE 16MGPLAQUENIL 200MGPREDNISOLONE ACETATE 1%PROCARDIA 10M GPSORCON 0.05 %REGITINE 5M GTHIOGUANINE 40MG

THIOTHIXENE 1MGTOPICORT 0 .25%VASOCON REGULAR 0.1% OPHTH

30346262253

25605713726523547342885435641037820

51657514584718069

31272818952234975

52707717020

377754

68890368889546687058909352654

26285750995015476599150

28571842979517606522818944110552985

897504753418235119

12

3456789

1011121314151617

181920212223242526272829303132

333435

Line Num ber Item # Descrip t ion Total Quant ity Unit Price ($) Total Cost ($)

that instructions for producing the ex-ception reports are protected by copy-right, private use exempted.) Just asany line item with a quantity of 1should be scrutinized for elimination,so should the same argument be m adefor line items with quan tities of 2, 3, 4,and so forth. The problem is how todetermine an appropr ia te cu to ff quantity. Sort-based analysis pro-vides a logical basis from which tom ake this cutoff. The first step in d e-termining the cutoff is to begin withthe data set after exception reports 1through 3 have been generated. Re-compute the sums for all the unitprices, quantities, and total costs andthen the cumulative percentages foreach of the inventory parameters.Next, sort the line items by total an-

nual inventory quantity in descend-ing order. Use as the secondary sortthe total annual cost in descendingorder. At this point, the PODR foreach of the three parameters shouldalso be calculated. Next, the grap hinginstructions provided in the pr evioussection should be applied.

The graph should be displayed onthe computer screen in the largestmagnification that the spreadsheetsoftware will allow. Evaluation of th egraph should begin at the top rightcorner of the grid and p roceed to theleft along the curve for cumulativepercentage of the total cost. Thiscurve is to be evaluated to d eterminewhether the tail of the curve for cu-mulative annual cost exhibits uni-form waves or non specific irregulari-

ties. Figures 8 and 9 ar e used to illus-trate the difference between uniformwaves and simple irregularities. Fig-ure 8 is a graph of the last 40% ofinventory line items sorted in de-scending order of total quantity forthe medical center. The secondarysort was for total annual cost, also indescending order. The graph con-tains grid lines in a 10% square pat-tern.

The wavy pattern of the line fortotal annual cost is caused by anabrupt increase (acceleration) inslope. Because of the sorts used insort-based analysis, the increase inslope will occur only when the quan-tity changes from the previous lineitem and the correspondin g total costfor the line item exceeds the PODR


11/17


PRIMERS Inventory

Figure 7. Exception report 3, page 1 inventory i tems with a total quant i ty of 1.

50.353.96

90.49

3.845.039.09

28.36377.91

7.5716.7973.08

1.11118.02

11.57157.32

24.8024.8078.91

1.7719.2973.6561.98

7.258.21

90.0115.15

119.95189.99

22.5541.92

0.9934.07

238.506.0415.5215.9413.3731.99

6.19416.08137.08

58.108.56

58.1218.1111.7651.96

71.307.49

16.16

50.353.96

90.49

3.845.039.09

28.36377.91

7.5716.7973.08

1.11118.02

11.57157.32

24.8024.8078.91

1.7719.2973.6561.98

7.258.21

90.0115.15

119.95189.99

22.5541.92

0.9934.07

238.506.0415.5215.9413.3731.99

6.19416.08137.08

58.108.56

58.1218.1111.7651.96

71.307.49

16.16

111

111111111111111

11111111111111

111111111111111

111

AK-FLUOR 10% 5M L SDV OPHTHASPIRIN/CODEINE 30MGAZACTAM 1GM 15M L

BACLOFEN 1 0M GBAGS BRN 3LB 500BAGS CLR ZIPLK 2ML 4 X6BAGS TRD Z PLK CLR 3X5 4MMBAYRAB SDVBD 309 585 SYR ONLY 3CC 100BENZTROPINE MESY 1M GBETADINE SURGI-PREP BRUSHBORIC ACID PDR NF 4OZCALCIUM DIS VERS 200M G/5M L 5CARISOPRODOL 350MGCEFOTAN INJ 1GM 15M LCHEMO SAFTY GLV P/F 18MILCHEMO SAFTY GLV P/F LGECHEMO SAFTY BAG 12X15 4MILCHLOROPHYLL 3MG CHEWCHLORPROM AZINE 50 MGCIMETIDINE 400M GCLORAZEPATE 3.75MGCOLCHICINE 0.6MGCORDRAN .025%COREG 25MGDAPSONE 25M GDDAVP INJ 4MCG/M L 1MLDECLOMYCIN 150MGDEMULEN 1/50 28-DA YDEPO-MEDROL 40 M G/M L 1 M LDEXAMETH .25GMDEXT 10% IN J 5ML

DIDRONEL IV 300M G/6M LDILAUDID 2MG/ML 1M LDILAUDID 4MGDILTIAZEM HCL 60MGDOCUSATE SOD 50MG/5MLDOPAMINE 200MG D5W 250M LDUOFILM WART REMOVERENDRATE 150M G/M L 20ML AM PFLUORESCITE 10% 5ML AMPGABITRIL 4MGHALOPERIDOL 2M GHC CATH URETHR A/ P 18FR 94HC CONV 17847 3 CNVX WAFERHC MA SK MOLD ED D ISPHIB TITER 4X1 DOSE

INDIGO CARMIN E 0.8% 5M LKERR 738 DROPPER BOTTLE 1KERR 739 DROPPER BOTTLE 2

363101741165744763

97584755889

3234774306373864676612

588491849893580530210260306001304295297150297168462309

74849170475951389586722686708514494972152238936141578613760422855156622

142307540955

806026132555998377192260621961399691106484458182640813919241928465355388111559142653598698

610204778803778811

123

456789

101112131415161718

1920212223242526272829303132

333435363738394041424344454647

484950

Line Num ber Item # Descrip t ion Total Quant it y Unit Price ($) Total Cost ($)

for total cost. Upon evaluation of thecurve for cumulative percentage oftotal annual cost from right to left,the point of the first uniform wavepatt ern is labeled A. The next po int islabeled B, the third p oint C. W hen agraph is viewed in this manner on acomputer screen, it is possible to

place the cursor at these points andprod uce a small pop- up window withth ex an d y coordinates for th e point.This enables the p harm acist, withou thaving to evaluate several hundredlines of data, to find the point on th ecurve at which t he wave begins with-in the b ody of the inventor y data set.

Figure 10 is a partial list of themedical center inventory and lineitems in and around point A. Point Ais at 48.91% of the line items in thedata set. Notice that the line item Zof-ran (ondansetron, Glaxo Wellcome)tablets 8 mg, 100 un it doses, has a totalquantity of 2 and a total annu al dollars


12/17


PRIMERS Inventory

Figure 8. Sort-based analysis with p rimary sort by to tal quant ity, in descending order, for the active

invento ry at th e m edical center. Points A, B, and C mark p oint s of rapid acceleration (steep slope) of

tot al cost. The breakpoint s are from 3 un its to 2 unit s for point A, 4 units to 3 u nits for poin t B, and 5units to 4 units for point C.

100

90

80

%C

umulativeInventory

Parameters

70

60

10090807060


Quantity

Unit price

Total cost

A

BC

of $3074.88. Notice also that the linedirectly above it is the last line itemhaving a total quantity of 3 units. Bydesign, sort-based analysis can beused in this manner to find signifi-

cant tran sition poin ts, such as pointsA, B, and C. The total annual dollarsspent on Zofran 8-m g tablets in u nitdose packaging is greater than thePODR for total cost. Therefore, thetransition from the line items with atotal quantity of 3 to the line itemswith a total quantity of 2 results in anabrupt acceleration in the curve forthe cumulative percentage of totalcost. If this transition point fromquant ity of 3 to quantity of 2 did not

correspond to an annual total costgreater th an th e PODR for total cost,the effect on the cum ulative percent-age of total cost would not be largeenough to be observed on the graph.

Notice also that the curve for cumu -lative percent age of unit cost, directlybelow the curve for cumulative per-centage of total annual cost, has aneven more dramatic accelerationwave. The curve for cumulative per-centage of unit cost is helpful in de-termining where a uniform waveshould begin on the curve for cum u-lative percentage of total cost.

Since the inventory data used tocreate the graph in Figure 8 were

sorted in descending order of totalannual quantity, and since the mini-mu m total annu al quantity is 2, it canbe determined that the quantity of 2has a large impact on the PODR for

total cost. Several of the line itemswith the quantity of 2 have a totalannual cost greater than the PODRfor total cost. Therefore, exceptionreport 4 has no line items for themedical center. There are still lineitems that should be removed fromthe active inventory data set, but themore complex sort-based analysisprocedures are beyond the scope ofthis art icle.

Figur e 9 represents the last 25% ofinventory line items for the VA hos-pital pharm acy. The first po int wherea clearly visible wave can be seen inthe curve is labeled D (the first lineitem in th e tail where the total annualcost is greater than the POD R for to-tal cost for the VA hospital). Figure11 shows the list of inventory lineitems for the VA hospital at andaround point D. Point D is at lineitem 76.68%, with a total ann ual costof $8775 and an an nu al quantity of 7.The product is Risperdal (risperi-

done, Janssen) 3-mg tablets. There-fore, all annual quantities greaterthan or equ al to 7 are presumed to beimpor tant an d are retained in the ac-tive inventory data set. All items o f 6units or less were separated from thedata set and are listed in exceptionreport 4 for the VA hospital. It can-not be overemphasized that the pur-pose of an exception r eport is that thereport can be evaluated by a pharma-cist. Upon evaluation, the pharmacists

determined that there were many im-portant items in the quan tity range of 5and 6. Therefore, these line items werereturned to the active inventory dataset. As a result, the first gross cut atevaluating exception report 4 resultedin item s of 4 units or less being includ-ed in this report. Exception report 4included 305 line items for th e VA hos-pital and no ne for the medical center.Figure 12 is the first page of exceptionrepor t 4 for the VA hospital.


13/17


PRIMERS Inventory

Figure 9. Sort-based analysis wit h p rimary sort by to tal quant ity, in descending order, for the activeinvento ry at th e Veterans Affairs hospital. Point D m arks the first po int w here a rapid acceleration

(steep slope) of tot al cost is observed. The breakpoint o ccurs from 7 units to 6 units at po int D.

100

95

90

85

%CumulativeInventoryParameters

75 80 85 90 95 100


QuantityUnit price

Total cost

D

Figure 10. Inventory line items correspon ding t o the area around p oint A in Figure 8. The product representing po int A is high lighted in gray.

3.153.042.942.852.371.551.26

3074.881693.641687.151613.941099.601032.66

892.09

33333332222222

1.051.32

00.950.79

16.110.42

1537.40846.82858.08831.87547.94442.34457.92

TOLNAFTATE SOL 1% 10M LBETHANECOL TAB 5MG 100SLIM FAST STRAWBERRY 15OZBLEPH 10 OPHTH S 10% 15 MLHYDRAMINE ELIX 4OZMICRO K EXTND 10 M EQ 10 0GOODY 3328 PONYTAIL BANDS 1ZOFRAN TAB 8M G 100 UDR GEN 10 300M L/500M L 10X500MLZOLOFT TAB 100M G 500PULMOZYME INH 2.5ML 1M G/M LDIFLUCAN TAB 100MG 100UDHETASTARCH 6% 500M L 12CEFZIL TAB 500M G 100 1 00

3177318131863189319432093211205350351367513545616

84.6984.7284.7584.7984.8284.8584.8884.9184.9484.9785.0085.0385.0785.10

Total Cost ($)Total Quantit yLast Un itPrice ($)DescriptionIndex #% Line Item s

A

Before further adjustment by apharmacist, exception reports 2, 3,and 4 resulted in an active inventoryof 1775 line items for the VA hospi-tal, representing a 20% adjustment.

The active inventory for the medicalcenter resulted in 3214 line items,also repr esenting a 20% adjustm ent.

In ven tory refinem ent. With th e ex-

ception reports generated and aworkable active inventory estab-lished, the process of refining the in-ventory can begin. The inventory re-finement procedures described here

are limited to economic consider-ations only. With the active invento-ry in descending order of total cost,the PO DR for total cost (in this case,

$3409) should be used to separate th eactive inventory into the head andtail of its curve. The head (the itemsgreater than or equal to the PODRfor total cost) will have substantially

fewer items than the tail (the itemsless than th e PODR for total cost)in th e example, 14% of line items ver-sus 86%. The head can be describedas the replacement subset of the ac-tive inventory. Using a lower-costdrug, from the head or the tail, inplace of an equivalent higher-costdrug in th e head will produce appre-ciable savings in drug costs. Mosthealth-system pharmacies do an ex-cellent job of man aging therap eutic in-terchan ges for these most costly item s.The pharmacy department can usesort-based analysis to quantify anddocument the total savings generated.

The tail can be described as theelimination subset of the active in-ventor y. Elimin ating drugs from thetail will yield appreciable economicsavings in inventory managementcosts. The tail may contain therapeu-tic alternatives needed within thehead. Managing to redu ce the size ofthe tail can result in reduced staffing

requirements for the pharmacy de-par tment and increase avai lab lespace.

When the m echanics of the inven-tory problem are presented in thismanner, it helps focus other health-


14/17


PRIMERS Inventory

Figure 11 . Inventory line items correspon ding t o the area around p oint D in Figure 9. The product representin g po int D is highlig hted in g ray.

332625242215

9877541372670261022662089

835

88888887777777

4333321

1254591381373324298119

PROPYLTHIOURACIL 50MGEPHEDRINE SULFATE 25MGDEMEROL 50M GPIROXICAM 10 MGSORBITOL 70%LOXITANE 5M GALBUTEROL SULF 2M GRISPERDAL 3MGRISPERDAL 1MGBREVIBLOC 250M G/M L 10M LPRIMAXIN I.V. 500M G VIALZOFRAN 8MGLUPRON DEPOT 7.5MGMESTINON 60MG

13862822921

35967922343

89763778038777399463339663334772672956754

258814574616214270

76.3576.3976.4476.4976.5476.5976.6376.6876.7376.7876.8376.8976.9276.97

% Line Item s Index # Descrip t ion Last Unit Price ($) Total Quan t it y Total Cost ($)

D

system professionals on inventoryand formulary economics. The eco-nom ic presentation h elps form a log-ical, unbiased platform from whichto focus the various health-systemprofessionals on th e formu lary prob-lem. The exception reports are also apart of this economic presentation.The activity clues generat ed in the ex-ception reports directly influence themore detailed process of inventoryevaluation. A more complete evalua-

tion is accomplished by performingactivity-based analysis.

App lication of activity-basedanalysis

Activity-based analysis requiresobservation an d inqu iry and can leadto im portan t chan ges in perspective,as observed in the case stud ies repor t-ed in this section. To aid in the dis-cussion, it is helpful to define someimportant terms used in activity-

based analysis.A job shop is an activity centeredaround producing or managing a lowvolume of items that vary greatly. Anexample of such an activity is the p rep-aration of i.v. antineoplastic agents.Each i.v. solution is custom-tailoredfor each patient and therefore variesgreatly. The volume of people requir-ing this service is low, however.

A flow shop is an activity centeredaround producing a moderate tolarge volume of items that are rou-

tine. An example of such an activitywould be th e preparation o f i.v. solu-tions for intermittent infusion in-tended for administration through-out the health system.

An inventory activity is the effectthe job shop, flow shop, or some oth -er event has on the way inventorym oves or flows in the facility.7

To help identify job shops or flowshops within the pharmacys activi-ties, it is helpful to iden tify som e dis-

tinguishing characteristic of the in-ventory activity. Activities that affectinventory management could in-clude ambu latory care inventory, di-saster inventory, universal inventory,decentralized inventory, code in-ventory, and emergency departmentinvento ries. As a start, distinguishingbetween those inventory line itemsthat are used exclusively for inpa-tients and those that are used exclu-sively for outp atients is recomm end-

ed. Assign the value of 1 to an inpa-tient-only drug and the value of 2 toan outpatient-only drug. It is then asimple matter for a pharmacist totake the spreadsheet containing thelist of dru g line item s and to assign anappropriate value to each (1, 2, orno value). Most of the line itemsreviewed will be assigned no value.Next, the data set m ust be sorted, inascending order, with the columnthat contains the inpatient and out-patient values (primary sort). Go to

the bottom of the list and insert rowsbetween th e line items th at representthe inpatient and outpatient lists.The drugs that have no entry will re-main at the top of the list. From Ta-ble 1, the VA hospital had 427 out pa-tient-only drugs. As it turns out,these 427 inventory line items repre-sented 35% of the total quantityman aged by the VA hospital pharm a-cy. The fact that they representedonly 9.5% of the annual cost of the

inventory line items in no way di-min ishes the imp ortance of the man-agement cost to the pharmacy de-partm ent. Remem ber that quantity isthe impor tant cont rol aspect with re-spect to inventory man agemen t.

The inpatient-only drugs repre-sented 102 line items, for a total of1% of the total quant ity of dru gs han-dled by the VA pharmacy. However,these 102 line items represented 4%of the total ann ual cost.

The medical center statistics forinpatient and outpatient drugs aremuch different. The medical centerhas no outpatient-only drugs. Theinpatient-on ly drugs represented 117line items, for a total of 20% of thetotal quant ity of dru gs hand led by themedical center pharmacy. These 117line items repr esented 22% of th e to-tal ann ual cost. As one would expect,the results are consistent with thevery different patient mixes of thetwo facilities examin ed.


15/17


PRIMERS Inventory

Figure 12. Exception report 4, page 1 Inventory item s wit h a total quant ity of 2, 3, or 4.

128.2841.8474.4466.5211.04

655.92399.60255.32

69.0838.1646.8048.3272.52

1754.80106.32173.04

35.60

1012.6812.2082.20

503.6452.52

340.24485.28475.96

47.6868.0830.84

215.16115.24

13.521.72

751.0838.2472.4464.88

181.6093.1287.2439.0067.6470.4870.4881.04

270.52736.04122.12

7.6014.2489.52

32.0710.4618.6116.63

2.76163.98

99.9063.8317.27

9.5411.7012.0818.13

438.7026.5843.26

8.90

253.173.0520.55

125.9113.1385.06

121.32118.99

11.9217.02

7.7153.7928.81

3.380.43

187.779.56

18.1116.2245.4023.2821.81

9.7516.9117.6217.6220.2667.63

184.0130.53

1.903.56

22.38

44444444444444444

444444444444444

444444444444444444

ACCUCHEK CMFRT CURVE STRIPALLOPURINOL 100MGBACLOFEN 1 0M GBENZTROPINE MESY 2M GCAPSAICIN .025%CEPTAZ 1GM 25M LCHEMO SAFTY CONT YELLOWCIMETIDINE 300MG 5M LCLOBETASOL PROPIONATE .05%CLOROX LIQ BLEACH 64OZCOMPAZINE 5MG/ 5MLCORTEF 10M GCROLOM 4% OPHTHCYTOVENE 250MGCYTOXAN INJ 20 0M G LYOPHDEBRISANDEPO-MEDROL 80MG/ML

DIGIBIND 10M G/M LDIPHENHYDRAMINE 25MGDOBUTAMINE 12.5MG/ ML 20 M LDOSTINEX .5MGDROPERIDOL 2.5MG/ML AMPELDEPRYL SOMERSERGAM ISOL 5 0M GERGOLOID MESYLATE 1MGESTRADIOL 1MGFERRIC SUBSULFATEFLUORETS OPHTH STRIPSFLUOXYM ESTERONE 10M GFUROSEM IDE 10MG/ ML 4 ML SDVFUROSMD E 40MG/4M L 22GGENOPTIC SOP .3%

HALCION .25MGHC CONV 1756 35 TAIL CLOSU BXHC CONV 17847 5 CNVX WAFERHC CONV 401544 POUCH UROSHC CONV 650832 POUC UROS BXHC CUNNINGHAM CLAMP REGHC HOLL 3669 POUCH DRAIN BXHC HO LL 3722 BARRER 2PC BXHC HOLL 3834 POUCH DRAIN BXHC HOLL 3892 POUCH DRAIN BXHC HOLL 3894 POUCH BXHC HOLL 980 4 LEGBAG STRAP BXHIPREX 1GMINOCOR 5MG/ ML 20M LISUPREL INJ 1/5 M AM PUL 13JJ BAND-AID FLEXIBLE ASSTLABEL 1-77G LAST REF ON RLESCOL 40MG

93440663217414545858850942514057612

623660428748815506601096232652257485428847424481668525766899797886

663104251793936658681510659912693481593616475970650929677195776302936492926238117291892695

963991472944111575701839649913598821836874131789171397324145427484951038210609435586284885939173921692356626

123456789

1011121314151617

181920212223242526272829303132

333435363738394041424344454647484950

Line Num ber Item # Descrip t ion Total Quan t it y Un it Price ($) Total Cost ($)

It was determined that the num-ber of inpat ient p icks for th e VA hos-pital was around 300 per day and thatoutpatient picks were around 2000per day. For the m edical center , it wasdetermined that the n umber of inpa-tient picks was around 2800 per day

an d th a t o u tp a t i en t p i ck s w ere

around 300 per day. The inventoryactivity resulting in the disparity isattributable to the nature of the VAhospitals relationship with its pa-tients. Because of its obligation toveterans, the VA hospital system isresponsible for providing nonpre-

scription drugs to its patients. These

nonprescription drugs are a largecomponent of the outpatient-onlydrugs.

At this poin t, activity-based an aly-sis has directed us to an interestingdifference between the two healthservice facilities. For the VA hospital,

a consequence of its outpatient drug


16/17


PRIMERS Inventory

obligation is the opportunity to de-velop a flow shop specifically de-signed for effectively dispensing ou t-patient-only drugs. The flow-shopmeth od m ay be the most practical for

nonprescription drugs and pharma-ceutical supplies. A flow shop that ac-counts for 35% of a pharmacys ac-tivity is an important observationone that can, it is hoped, be trans-formed into substantial cost savings.

For the medical center, a similaropportunity may exist for inpatient-only drugs, depending on the whole-saler involved. Many wholesalers of-fer options for custom packaging.Items pu rchased can be packaged inspecial containers according to theirultimate destination in the healthsystem. These special containers canbe delivered to the ho spital pharmacywithout requiring immediate break-down of the package. In this way, thespecial cont ainer can b e delivered di-rectly to th e satellite pharm acy or au -tom ated dispen sing device where it isused. Such a strategy avoids han dlingcosts in the main pharmacy andspeeds delivery to the ultimate desti-nation.

It should be n oted th at exercisingsort-based and activity-based analy-ses does not help the pharmacy de-partment determine when a produ ctshould be purchased and how much.Although sort-based and activity-based analyses make inventory con-trol and inventory purchasing issueseasier to resolve, a thorough discus-sion of these inventory issues is be-yond the scope of this article. Anoverview of the con cepts is provided,

with an emphasis on perpetual in-ventory systems.

Perpetual inventory

There are two management con-cerns associated with inventory pur-chasing: when to order and howmu ch to order. When to order can bedetermined by three methods: (1)perpetual inventory monitoring, (2)fixed period or cycle ordering, and(3) flagging methods. An under-

standing of the effect of the amountordered is rooted in economic ordertheory.8-10

Perpetual inventory systems re-quire the inventory quantity on hand

to be recomp uted as each unit of in-ventory is used. It is by far the mostexpensive method for managing in-ventory. An example of a perpetualinventory system is the automateddispensing devices used in the con-trol of narcotics or other drugs. Itwould be too expen sive to m anage allinventory line items with the sameprecision as those managed by theperpetual inventory system used byan autom ated dispensing device. Thisobservation m ight lead the r eader tobelieve that perpetual inventory sys-tems are on ly for those items that r e-quire a great deal of security or thathave very high value, but this is notnecessarily true. For example, con-sider th e checkout coun ter at th e lo-cal grocery store. In the grocery store,the perpetu al inventory system is jus-tified because of the high volume ofactivity, regardless of the p rice of in-dividual items.

The essential element, as well as

the inh erent expense, of perpetual in-ventory systems is the requirementfor accurate feedback. With an auto-mated dispensing device, the feed-back is provided by the data entryand data verification performed bythe u sers. In th e grocery store setting,feedback is provided by the bar codeon the products and the scanner atthe checkout co un ter. As results fromthe sort-based analysis indicate, mostdrug inventory items do not have

enough volume (acceleration) tom ake this plan worth while. More im-portant, available methods of feed-back are not sufficiently reliable tomake large-scale application of per-petu al inventor y cost-effective.

However, the identification of thenon prescription dru g activity (a sub-set of the outpatient-only drugs) atthe VA hospital is conducive to aperpetual inventory system. Becausemost of the items identified in the list

of 427 outpatient-only drugs have barcodes already installed on their pack-aging, a com plete feedback loop can beachieved without the cost of applyingbar codes. The pharmacy would incur

only the cost of a scanner.By performing activity-basedanalysis, it is possible to determineoth er areas th at h ave sufficiently reli-able feedback to make a perpetual in-ventory system worthwhile. Onemeth od of determ ining the activitiesthat are suitable for perpetual inven-tory requ ires sort ing the line item s bythe total annual cost in descendingorder. From that list, select a verysmall portion of the most importantline items. The VA hospital data ( Fig-ure 13) were used to determine that6% of the inventory line items ac-counted for 70% of the total annualcost. This point is labeled E on thecurve for cumulative percentage oftotal cost (red). There are only 108line items in this data subset. Thisinventory subset has a suitably smallnum ber of items to b egin an activity-based analysis on an item-by-itembasis in order to determine whichitems have a sufficiently reliable feed-

back loop for a perpetual inventorysystem to work.

The number of items used to ini-tiate a perpetual inventory systemshould be kept small. Attempting toinclude a large number of items in-vites failure. With a small number ofitems in the system, it is much easierto use a truly experimental formatwith which to test the results. Theactivity-based an alysis can be used todetermine the actual physical trans-

portation and destination patternsincurred by this small subset of theactive drug inventory. Also, themethod through which feedback isprovided to the perpetual inventorycompu ter system can be m ore closelymo nitored. For some dr ugs, the feed-back to the system m ay com e from asmany as five to eight different areasof activity within a health system.This could mean that the data con-tained within five to eight computer


17/17

PRIMERS Inventory

Figure 13. Sort-based analysis with prim ary sort b y to tal cost, in d escending order, for the active

invento ry at the Veterans Affairs hospital. Point E marks the po int w here a convenient subset of t he

active inventory head is selected for use in an activity-based analysis focused on perpetu al invento-ry activity. Point E represents 70% of t otal cost incurred b y 6% of in ventory line item s.

100

80

60

%C

umulativeInventory

Parameters

40

20

0 20 40 60 80 100


0

QuantityUnit price

Total cost

files must always be accurate or theperpetual inventory count for thoseitems will not be accurate. On the oth-er han d, if a dru gs activity is accoun t-ed for by only one or two files, then it ismore likely that the perpetual invento-

ry system for that item will be accurat e.If too many line items are included inthe startup of the perpetual inventorysystem, these fine distinctions will belost in the complexity caused by sizeand nu m ber of files.

Conclusion

Modern inventory analysis tech-niques that take annual quan tity, unitprice, to tal annual cost , and thehealth systems unique activities into

consideration provide the pharma-cist with a practical basis for invento -ry management. Managing the com-plexity of large inventory problems isbest achieved through methods de-signed to divide the inventor y prob-lem int o m anageable compo nents.

aQuantitative proof is available from theau thor .

References

1. Musashi M. A book of five rings. Harris V,transl. Woodstock, NY: Overlook; 1974.

2. Hotaling W. Inventory management. In:Nimmo CM, ed. Purchasing and inventorycontrol. Bethesda, MD: Am erican Society ofHospital Pharmacists; 1990:167.

3. Berger BA. Inventory management. In: Ef-fective pharmacy management: a compre-hensive presentation of practical manage-ment techniques for pharmacists. 5th ed.Kansas City, MO: Marion Laboratories;1989:220.

4. Heizer J, Rende B. Operations management.5th ed. Upper Saddle River, NJ: Prentice-Ha ll; 1999:441-2.

5 . Ibid. p 441.6. Berger BA. Inventory management. In: Ef-

fective pharmacy management: a compre-

hensive presentation of practical manage-ment techniques for pharmacists. 5th ed.Kansas City, MO: Marion Laboratories;1989:224.

7. Heizer J, Rende B. Operations management.5th ed. Upper Saddle River, NJ: Prentice-Hall; 1999:444,465.

8. Ibid. pp 446-65.9. Hotaling W. Inventory management. In:

Nimmo CM, ed. Purchasing and inventorycontrol. Bethesda, MD: Am erican Society ofHospital Pharmacists; 1990:168-72.

10. Berger BA. Inventory management. In: Ef-fective pharmacy management: a compre-hensive presentation of practical manage-ment techniques for pharmacists. 5th ed.

Kansas City, MO: Marion Laboratories;1989:222-4.

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