Effective Demand Forecasting in the Healthcare Supply Chain

8/19/2019 Effective Demand Forecasting in the Healthcare Supply Chain

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Effective Demand Forecasting In the Health

Care Supply Chain

By Timothy J. Callahan

David R. u!man" #$ens % &inor" Inc.

&ar' (. )an Sumeren" #$ens % &inor" Inc. July 16, 2004

The road to automated replenishment is not an easy one. However, through the integration of

intelligene, tehnology, and e!pertise, effetive demand foreasting in the health are supplyhain is attaina"le.

#nvision a senario in whih pressing the #nter $ey on a hospital omputer sets into motion a series of oordinated proesses that reahes aross the entire

health are supply hain % from the manufaturing plant, through transportationand distri"ution networ$s, to the patient %s "edside.

Through a areful integration of the hospital system %s diverse data, inluding

information aptured from linial, finanial, and operational soures, the

simple at of sheduling a routine medial proedure would ativate an automatedsystem that&

• 'hooses produts for the patient standardi(ed to the )*'+- proedure odes

• /ssesses the need for "a$up ontingeny supplies and produt options "ased

on physiian produt preferene and historial data

• i$s the supplies appropriate for that individual ase, and groups those

supplies with all other supplies needed for prep, reovery, and follow+up

• erifies the latest ontrat prie and ensures synhroni(ed priing auray

among all supply hain sta$eholders

• etermines whether there is a need to replenish supplies either at on+site

sto$ loations or in the off+site warehouses of a distri"ution partner

• /ggregates the produt replenishment re3uirements and automatially plaes

an order and

• 'ommuniates usage data to the manufaturer and other sta$eholders for prediting

future demand.


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*hat Else+

These proesses may well "e the vision of the future for the health are supplyhain % a world in whih medial and surgial supply purhases are unompromisingly

driven "y the demands of aregivers and their patients, "ut whih also em"raesthe most innovative and effetive onepts of demand foreasting, inventory

postponement, and automated replenishment $eeping supply hain osts under ontrol.*t is a world where tehnology erases the lines of distintion "etween diret

purhases and distri"ution, sending an aggregated purhase order that automatially

selets the most ost+effetive produt om"ination and routing through thesupply hain, and then segregates and delivers the order to the appropriate

reipients.

*t is a world where supply hain performane is measured end to end, analy(ingdown to the 57loation level, dramatially reduing the need for on+hand inventory

for sheduled medial proedures and where health are information not normally

assoiated with the supply hain, suh as aggregate patient data, medial researh,

demographis, and the hospital%s own strategi o"8etives, is integrated toe!tend demand predita"ility into the future.

This Future Is *ithin Reach

Today, there are three fators that ma$e this vision of the future attaina"le&

the a"undane of untapped information already availa"le in the hospital settinga methodology of demand foreasting developed in other industries, "ut whih

an "e adapted to health are and the reent growth and maturation of someinformation tehnologies that ena"le an unpreedented level of integration of

data from diverse soures.

*ntegration of linial data into the supply hain e3uation will revolutioni(e

the management proess, ena"ling us to transform the e!isting yet often segregatedmi! of information into ationa"le intelligene for health are deision ma$ers.

ni3ue and ustomi(ed appliation of some proven priniples of supply hain

management from the retail industry, and some reent tehnologial advanes,

will gain health are supply hain effiienies that we have "een antiipatingfor years. These effiienies, in turn, will open the door to numerous orollary

"enefits suh as improved patient safety, more favora"le linial outomes,

revenue enhanement, and an even more healthful wor$ environment for liniians.

Health Care Is ,ot Retail


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This is not the first time the health are industry has onsidered applying

retail demand foreasting strategies. These onepts are well+proven, and have

"een around sine the late 190s, when health are e!eutives first used themin efforts to standardi(e, manage, and pa$age produt in patient+ready )onsumer-

onfigurations. *n health are, those efforts met with some suess. roponents

found they ould wor$ well to support limited proedures and volume, "ut oftenfailed to over ontingenies liniians fre3uently enounter at the pre+op,

proedural, and reovery phases.

Having inorporated these lessons into the lore of supply hain management,

we ontend that our industry is now ready to develop its own set of priniplesthat draws upon the onepts of retail demand foreasting models, "ut whih

fully aounts for the uni3ue nature of health are % in whih a failure to

meet the demands of onsumers )patients and liniians- an have dire onse3uenes.

/dvanes in tehnology, historial trending, surgial sheduling, and linial

information systems have given us the a"ility to manage usage more effetively.The integration of supply hain management systems with point+of+use data entry,

and improvements in inventory management )suh as the emerging :;* tehnology-,are ena"ling us to lear the way for the final and most important step in the

integration of health system data % lin$ing the linial pathways harted in

advaned patient data to the supply hain deision+ma$ing proess.

-roecting Demand (ccurately Is the /ey

*n the retail industry, one of the most ommon hallenges faing e!eutives

is a la$ of relia"le information for prediting what ustomers will "uy. :etailstores sto$ their shelves "ased on a om"ination of intuition, e!periene,and mar$et researh that is often highly speulative. *t is a ris$y proposition,

espeially for the "uyer responsi"le for filling warehouses that serve thousands

of retail outlets. The proliferation of learane sales at the end of eah "uyingseason attests to the odds for failure.


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shelves may "e su"stantially greater than in almost any other industry % at

least for ertain su"groups of their total annual purhases. =here else "ut

in a hospital an a manager wal$ in and loo$ at a shedule that tells the num"er of ustomers and the potential produt demand with relative auray for that

very day@

To date, efforts to automate the health are industry have "een admira"le.

>ost hospitals now have automated systems in plae to tra$ diagnoses, medialevents, patient satisfation, purhasing, aounts paya"le, reim"ursements,

surgial team preferenes, dispensing of pharmaeutials, and more. nli$e the

retail environment, however, the prinipal hallenge in hospital systems isnot a la$ of relia"le information to support deision ma$ing, "ut rather the

la$ of visi"ility and integration of data that is already there % data that

is routinely gathered "ut stored in diverse information systems that rarelyommuniate with eah other in meaningful ways.

=ith so many data soures, and so many advanes in tehnology and analytialapa"ilities, there ould "e "oundless possi"ilities for a health are institution

apa"le of organi(ing and using its information to gain "usiness and linialadvantages. ltimately, the goal should "e to reate a health are supply hain

that is apa"le of $eeping the liniians supplied, and at the same time, limiting

on+hand inventory to what is neessary to address ontingenies.

#n the Road to (utomated Replenishment

Hospitals are aross the "oard in their level of sophistiation in supply hain

management, ranging from failities% systems that still tra$ physiian prefereneson inde! ards, to systems that are managing the supply hain with advanedmethodologies suh as ativity+"ased osting, *nternet+"ased analysis of purhasing

and utili(ation, and outsouring the management of supply a3uisition in high+dollar

linial units.


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• /ppliation of these new management methods to reate a linially driven

demand hain supported "y low on+hand inventory and automated replenishment

and

• The appliation of this e!panded supply hain intelligene for 3uality improvement

and reim"ursement optimi(ation with the health system.

Figure 1. Potential Sources of Information to Support Effective Demand Forecasting

in a Health Care System

E0panding -roven )alue

#!periene has shown already that integrating and analy(ing the data within

a single management system, suh as hospital purhasing, an reap su"stantial

"enefits. *nternet+"ased mining of routine purhasing data, when properly analy(ed,an produe information that forms the "asis for om"ining purhase orders,

standardi(ing produts, reduing inventory, and improving ontrat ompliane

% all proven strategies for reduing osts. Aot only that, analysis of supplyhain ativities has ena"led the reation of models that more appropriately

determine atual supply osts. *ntegrating supply hain information with a hospital%s

linial, finanial, and human resoures information systems offers an opportunityto analy(e relationships "etween supply utili(ation and other important measures


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li$e la"or osts, reim"ursement levels, and patient outomes. uh analysis

ena"les health are systems to identify the ost of are at the episode level,

deteting variations from the norm "y liniian and proedure. otential "enefitsare immediate, inluding a redution in the need for linial employees to tra$

and manage inventory, and apturing supply onsumption as a part of linial

doumentation.

Forecasting Demand

By integrating linial information systems, the health are system an lin$

utili(ation to outomes and provide more aurate linial doumentation, whih

immediately offers the potential to improve harge apture and redue reim"ursementdenials. The hospital e!eutive, or the hospital%s supply hain partner, has

relia"le information to reate a realisti "ill of materials for proedures

from the preparation phase through reovery and follow+up.

*n speifi loations, suh as the surgial suite, 5+ and loation+speififoreasting tehnology an "e used to synhroni(e surgeon preferene information,

and predit demand "ased on the hospital%s sheduling, patient demographis,

and even seasonal demands % with the onse3uent "enefits of redued inventorylevels in the ?:, lower osts for ase preparation, and improved fill rates

and servie levels. *n many ases, hospitals are li$ely to e!periene inreases

in linial satisfation, produtivity, and patient safety as well.

Beause the ris$s assoiated with health are are unli$e those of any other industry, the 3uality of demand foreasting must "e impea"le. The proess

must&

• ro8et demand "y loation and 5 and address long+term and short+term

needs

• upport the hospital%s "udgeting and planning proess to aount for introdution

and e!pansion of medial7surgial programs and

• /ddress the importane of the ritial lead times that are inherent and

essential in the health are environment.

(utomated Replenishment*n effet, this approah would onvert the onventional medial7surgial supplyhain into a %demand hain,% in whih information from many soures atually

drives the produt flow. ?riginating at the patient%s "edside, the information

flows through the demand hain "a$ to the prodution plant, where relia"ledemand foreasts ena"le manufaturers to ma$e intelligent prodution deisions.

The distri"utor uses the same information to redue oversto$s and produt shortages,


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and "oth the manufaturer and the distri"utor feed supply hain intelligene

"a$ to the hospital in the form of an effiient produt flow.

=hen the a"undane of information in a health are system is properly analy(edand applied to a well+tested demand response model, the ris$s assoiated with

automation an "e redued to an aepta"le level in an environment that mustallow for emergenies, and annot ompromise patient safety. *n this environment,

automated replenishment must also "e impea"le % ensuring appropriate, aurate,and on+time ordering tied diretly to linial demand, and inorporating proesses

to&

• Tra$ and report e!eptions

• etermine proedure+speifi lead times for re+orders and

• Be self+orreting.

Improving 1uality and Enhancing Revenue

#ffetive demand hain management produes tangi"le hanges in the traditional

supply hain % most nota"ly the ost savings from inventory redution and postponement,

"ut there are many additional "enefits from this approah of gathering informationfrom diverse soures within the health are system. The heightened visi"ility

of the demand hain ena"les hospitals to identify opportunities for improving

patient outomes. *t also allows "etter ase doumentation to support revenue

enhanement.

The Demand Chain Continuum

espite many advanes in supply hain management, too muh of the medial and

surgial inventory in health are onsists of slow+moving 5s with a high ris$ of o"solesene, e!piration, damage, or reall. =ith ade3uate safeguards for

proteting patient identity, pressing the #nter $ey to shedule a partiular

medial proedure an generate speifi lists of medial7surgial supplies neessaryfor every stage of a proedure % ta$ing into aount preferenes of the liniian

patient attri"utes suh as age, weight, se!, medial onditions, and allergies

and predita"le e!ternal fators that influene the utili(ation of supplies.

Together, a fine+tuned foreasting system and automated replenishment proessan prepare the hospital for every sheduled proedure, redue the osts for

suh proedures through standardi(ation, and help ensure favora"le outomes.

These systems also an help pro8et the li$elihood of unsheduled ases andune!peted auity issues, and determine the neessary produt mi! for "a$up

and support.


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Effective Demand Forecasting in the Healthcare Supply Chain