2011_the use of algorithms in assessing and managing persistent pain

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It’s no secret that greater numbers of Americans areliving longer than ever; and with advancing age,many will find themselves dealing with persistent,often debilitating pain. Nurses in all health care set-

tings can expect to be caring for increasing numbersof such patients. Yet experts acknowledge that pain inolder adults often goes underrecognized and under-treated.1 Algorithms—step-by-step guides—for pain

assessment and management might help nurses andother clinicians begin to change this situation.

Over the last 50 years, the average life expectancyfor a U.S. citizen has increased from 69.7 to 77.9 years,according to the Centers for Disease Control and Pre-vention.2, 3 The proportion of citizens ages 65 years andolder is also rising; experts predict that by 2030, olderadults will constitute 20% of the population—about71 million people.4 Moreover, about 80% of olderAmericans are now living with at least one chronic ill-ness.4 For older adults, the persistent pain often asso-ciated with chronic illnesses is of particular concernbecause of its detrimental effects on functioning andquality of life.

Research indicates that there is a high prevalenceof persistent pain among both community-dwellingolder adults and nursing home residents.5-7 Pain associated with osteoarthritis of the hand,8 back,9 and hip andknee joints10, 11 plays a major role in significant func-tional decline in older adults. A study in people ages80 and older who reported daily pain from variousconditions found that, as pain severity increased, mus-cle strength and physical performance progressivelydeclined.12 Another recent study found that older adultswho have persistent pain are at increased risk for falls;

the association held even after researchers adjustedfor underlying chronic illness and its treatment.13 This

34 AJN ▼ March 2011 ▼ Vol. 111, No. 3 ajnonline.com

Overview: As the U.S. population

ages, nurses will care for increas-ing numbers of older adults, most

of whom suffer from at least one

chronic illness. The persistent pain

associated with many chronic ill-

nesses can have detrimental effects

on patients functioning and quality

of life. Algorithms developed from

evidence-based clinical practice

guidelines are tools that can facili-

tate the application of research topractice. This article introduces

readers to the use of algorithms in

guiding the assessment and man-

agement of persistent pain in older

adults, and provides an illustrative

case study.

Keywords: algorithm, clinical

decision making, clinical practice

guidelines, evidence-based practice,

nursing judgment, older adults, pain

HOURS

Continuing Education

2.9

By Anita M. Jablonski, PhD, RN,

Anna R. DuPen, MN, ARNP, ACHPN,

and Mary Ersek, PhD, RN, FAAN

The Use of Algorithms in Assessing and Managing Persistent Pain in Older Adults

An introduction to tools that can facilitate

the application of research to practice.


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[email protected] AJN ▼ March 2011 ▼ Vol. 111, No. 3 35

Figure 1. Pain Assessment Algorithm

APAP = acetaminophen; NSAIDs = nonsteroidal antiinflammatory agents; UTI = urinary tract infection.

Go to the Pain

Assessment in

NonverbalPatient Algorithm

Treat the

etiology as well

as the pain

Conduct pain

character

assessment

Is the pain a

result of a

treatable etiology

(such as a

UTI)?

If pain is

NOCICEPTIVE

If pain is

MIXED

If pain is

NEUROPATHIC

Conduct

initial pain

assessment

Is the patient

currently

(in past 7 days)

experiencing any

type of pain?

No

No

No

No

Yes

Yes

Yes

Yes

If pain is mild to

moderate, go to

the APAP

Algorithm

or

If pain is

moderate to

severe, go to the

Opioids

Algorithm

and

If pain is from

acute inflamma-

tion or bony

metastases, go to

the NSAIDs

Algorithm

Go to the

Neuropathic Pain

Treatment

Algorithm

and

If pain is moderate

to severe, go to the

Opioids Algorithm

Can the patient

give self-report?

Reassess

as

appropriate

Does

treatment

resolve

the pain?


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is significant because falls are known to be a leadingcause of death and disability in the older popula-tion.14, 15

Since nurses spend more time caring for olderadults, in both community and residential settings,than do other health care professionals, they can bepivotal in ensuring that their patients’ pain is effectivelyassessed and managed. A nurse’s success in doing sowill depend on various factors, including her or hiscomprehensive assessment skills; knowledge of ap-propriate, evidence-based treatment strategies; anddecision-making ability. But basic nursing programsoften don’t adequately prepare nurses to care for olderadults or train them in how to apply best evidence topractice.16, 17

Algorithms developed from evidence-based clini-cal practice guidelines such as those published by theAmerican Geriatrics Society (AGS) and the American

Medical Directors Association (AMDA) are tools thatcan support and enhance nurses’ efforts to assess andmanage persistent pain in older adults. Although al-gorithms are frequently used by both physicians andnurses as aids in clinical decision making,18, 19 more ex-tensive use might facilitate the application of best re-search evidence to practice. This article describes whatalgorithms are and outlines their advantages and po-tential drawbacks when used in clinical practice. Twoalgorithms that focus on pain assessment and treat-ment with opioids are presented, along with an illus-trative case.

ALGORITHMS: AN OVERVIEW

Clinical practice guidelines are derived from rigoroussystematic reviews of the current literature; they syn-thesize scientific evidence and expert opinion into rec-ommendations for best practice. But it may not be im-mediately clear to a practitioner how to best implementthose recommendations. Algorithms offer clinicians amethod for doing just that.

An algorithm is a formula or set of rules for solvinga problem, according to Taber’s Cyclopedic MedicalDictionary; Stedman’s Electronic Medical Dictionary defines the term as “a systematic process consisting ofan ordered sequence of steps, each step depending onthe outcome of the previous one.” An algorithm canguide the assessment or management of a given clinicalproblem, define the possible end points, and help thenurse to determine the best course of action. Typicallyan algorithm is presented as a flow diagram, with sev-

eral branching pathways that lead to specified endpoints.18 For example, a nurse using the pain assessment

algorithm shown in Figure 1 will find a set of sequen-tial questions and instructions. Each question can beanswered “yes” or “no”; each answer directs the useralong a particular path and ultimately to a specific, rec-ommended action.

Advantages. Nurses make numerous decisionsevery day in clinical practice, the consequences ofwhich directly affect outcomes of care. Because algo-rithms guide thinking in a logical, step-by-step ap-proach, they can be used to refine nurses’ skills indecision making, and can help to reveal gaps in a par-ticular assessment or management process, as well aserrors in thinking about a clinical problem.18, 20 Algo-rithms can be especially valuable for novice nurses whohave less experience in decision making: they can helpthe nurse to make sound decisions and avoid flawedones, thereby increasing her or his confidence.

Many nurses haven’t been adequately prepared to

locate, interpret, and apply research findings and clini-cal guidelines to practice.21 Algorithms can be valuableteaching aids in addressing these deficits. Their visual,flow-diagram format has been shown to be effectivein promoting learning and adherence to best prac-tice.18, 19, 22

Lastly, algorithms can reveal areas in which furtherresearch is needed. In an algorithm based on clinicalpractice guidelines, the recommendations made at various decision points will be supported by various levelsof evidence. For example, the AGS’s guidelines for thepharmacologic management of persistent pain in older

adults advise that nonsteroidal antiinflammatory drugs(NSAIDs) be prescribed “rarely, and with extreme cau- tion, in highly selected individuals”; the recommenda-tion is based on strong, high-quality evidence such asthat from randomized controlled trials.5, 23 But sup-port for the use of nonpharmacologic methods (suchas the application of heat or cold, acupuncture, andtranscutaneous electrical nerve stimulation) is muchweaker, based on expert opinion or clinicians’ expe-rience.23 An algorithm derived from these guidelineswill reflect such differences in the strength and qualityof evidence, thus underscoring gaps and weaknessesin the knowledge base.

Drawbacks and caveats. Critics have argued thatalgorithms are rigid and encourage robotic decisionmaking.18 Some contend that algorithms don’t takeinto account all possible factors, such as comorbidities,medical and social histories, and potential drug-drug

interactions, that must be considered in making clin-ical decisions about treatment.18

Algorithms’ step-by-step approach can be used to refine nurses’

skills in decision making.


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But it’s not feasible to build all possible contingen-cies into an algorithm. An algorithm is designed tocover the likely contingencies for the majority of pa-tients with a given condition; still, individual differencesmust be considered. Moreover, to ensure high-qualitycare, patient preferences and values must also be in-corporated into evidence-based practice.24

Finally, a given algorithm—like the practice guide-lines it’s based upon—can only be as strong as the un-derlying evidence. Although many recommendationswill have been validated with high-quality, strong em-pirical evidence, others may necessarily be based onweaker evidence such as expert opinion. Thus, it’s im-portant to emphasize that sound decision making isn’ta rote process; and that while algorithms can be excel-lent guides for clinical decision making, they cannotsubstitute for careful observation and critical thinking.

TWO ALGORITHMS FOR ADDRESSING PAIN IN OLDER ADULTS

Two algorithms, one focusing on pain assessment andone on opioid therapy, are presented in Figures 1 and2. They are from a series of algorithms developed fora study, funded by the National Institutes of Health(NIH), to evaluate the efficacy of algorithms in assess-ing and managing pain in older adults who reside innursing homes. (All of us were involved in this study:ME was the primary investigator and AMJ and ARDwere coinvestigators.) Each algorithm in the series ad-dresses a major aspect of pain assessment and man-agement. There are separate algorithms for assessingpain in people who can and cannot self-report. There

are also algorithms to guide the use of specific types ofanalgesics (such as acetaminophen, NSAIDs, opioids,and adjuvant medications), as well as to guide assess-ment and management of analgesic-related adverse ef-fects (such as constipation, sedation, and nausea andvomiting).

The algorithms are based on the relevant, evidence-based clinical practice guidelines developed by theAGS and the AMDA.5, 23, 25 A panel of experts in geri-atrics and pain reviewed the initial drafts, and the finaldrafts were revised based on their critiques. First de-veloped in 2005, the algorithms were most recently up-dated in 2009. All of the algorithms were compiled ina reference manual and were tested during the interven-tion arm of the study. The study has been completedand data analysis is ongoing.

ILLUSTRATIVE CASE

Helen Gordon, an 80-year-old resident in a long-termcare facility, suffers from several chronic illnesses,including chronic renal failure; hypertension; osteo-porosis; and osteoarthritis, a progressive degenerativejoint disease that affects several of the patient’s joints,particularly her knees. (This case is a composite basedon our experience.) Until recently, she was able to walk

using a walker. But during the past week, Ms. Gor-don has frequently reported pain. She now relies on

a wheelchair to get around and requires moderate as-sistance with transfers.The nurse caring for Ms. Gordon recognizes that

pain is a significant factor in her patient’s limited mo-bility. The nurse isn’t sure which treatment will bemost effective in helping Ms. Gordon to regain herprevious level of independence. The first step towardmanaging her pain is a thorough pain assessment. Thenurse refers to the algorithm shown in Figure 1 toguide the assessment, beginning with the oval shapein the upper left-hand corner.

Pain assessment algorithm. Can the patient giveself-report? Answer: Yes.

As directed by the algorithm, the nurse first deter-mines that Ms. Gordon is alert and oriented and ableto report her pain. The algorithm next instructs thenurse to conduct an initial pain assessment. If Ms.Gordon had been unable to self-report, the algorithmwould have directed the nurse to use an algorithm de-signed for patients unable to self-report.

Is the patient currently (in past 7 days) experienc-ing any type of pain? Answer: Yes.

The nurse’s assessment, which includes a physicalexamination and patient interview, reveals that Ms.Gordon is experiencing moderate-to-severe, nonradi-ating, bilateral knee pain. Ms. Gordon reports that,until recently, this pain was mild to moderate and tol-erable; but during the past week it’s increased mark-edly. Asked to rate her current pain on a 0-to-10 scale,with 0 representing no pain and 10 representing theworst pain imaginable, Ms. Gordon rates her currentpain at 6; she adds that it’s usually worse in the morn-ing, often at 7 or 8. The pain is exacerbated with exces- sive movement and prolonged periods of immobility.Ms. Gordon is distressed by the adverse effect this painis having on her ability to function independently; forexample, she’s having difficulty showering and walk-ing to meals. She states that she’s depressed because

the acetaminophen she’s been taking is no longer ef-fectively relieving her pain.


Basic Elements of Pain Assessment

• Location

• Intensity

• Pattern (for example: constant, intermittent)• Duration

• Character (for example: sharp, burning, aching)

• Effect on physical functioning and mobility

• Effect on mood, social functioning, and sleep

• Factors that exacerbate and alleviate

• Current treatment regimen

• Adverse effects of therapy


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impairs function, or both. Ms. Gordon is already tak-ing up to 3 g of acetaminophen daily without satisfac-tory pain relief. She also rates her pain as greater than4 and has decreased function because of pain. Thusthe nurse determines that she may indeed require opi-oids to achieve effective pain relief, and continues tothe next step of the opioids algorithm.

Is the pain localized and affecting superficial struc-tures? Answer: Yes.

Superficial structures—structures relatively close tothe body’s surface—could include skin, mucous mem-branes, subcutaneous tissue, and superficial tendonsand ligaments. Ms. Gordon’s pain is nociceptive andlocalized in her knees, possibly as a result of increasedinflammation around the joints.

Has the patient been tried on topical analgesics? Answer: No.

Because Ms. Gordon’s pain is nociceptive and local-ized in her knee joints, it may respond well to topicalanalgesics, which haven’t yet been tried. The algorithmrecommends that a trial of certain agents be initiatedand the patient subsequently reassessed. The nurse ob-tains an order for a trial of a topical NSAID, diclo-

fenac sodium 1% gel, to be applied to both knees threetimes a day.

The strength of the evidence for some elements ofthe algorithm varies, as is the case here. Several top-ical agents can be used to treat pain, including lido-caine (Lidoderm and others), capsaicin (Capsagel andothers), and NSAIDs; topical preparations includecreams, gels, and patches. In general, strong evidencesupporting the use of topical analgesics, particularly fornonneuropathic pain, is lacking.5 But there is some evi-dence for the short-term efficacy of topical NSAIDs,26-28 although long-term efficacy hasn’t been established.29 Of the topical NSAIDs, preparations of diclofenac andibuprofen have been the most widely studied.26

The algorithm recommends an initial trial of a top-ical analgesic because they tend to have fewer adverseeffects and to interact less with other drugs than do sys-temic analgesics, making their use an advantage, especially in elderly people, who are more likely to havemultiple comorbidities for which they are receivingpharmacotherapy.26, 28 More research is needed to clar-ify the proper role of these agents in managing pain.

An order for diclofenac gel is faxed to the institu-tion’s contract pharmacy; but this agent isn’t on thepharmacy’s preferred formulary, so the recommen-

dation cannot be acted on. This barrier points out theneed for critical thinking when using an algorithm.

Is the pain a result of a treatable etiology? Answer:No.

The nurse asks Ms. Gordon whether she’s fallenor experienced other physical trauma in the last twoweeks; Ms. Gordon says that she hasn’t. She also statesthat although the intensity of her pain seems to beworsening, its location and quality are unchanged. Thefindings of the nurse’s physical examination are consis-tent with Ms. Gordon’s known history, and a review ofthe medical record (X-ray reports, physician notes) re-veals no evidence that Ms. Gordon’s pain results froma new or treatable source. The nurse concludes that thepain is probably the result of worsening osteoarthritis.Ms. Gordon receives medications for osteoporosis andrestorative therapies (including physical therapy andmassage) to slow the functional impact of osteoarthri-tis, but neither condition is curable.

As the algorithm indicates, the next step is for thenurse to further evaluate the character of Ms. Gordon’spain. (See Basic Elements of Pain Assessment .) Thisstep is crucial: the information gleaned from a system-atic and thorough pain assessment will help to deter-mine the appropriate treatment regimen, particularly

with regard to analgesics.Conduct pain character assessment: is the pain noci-

ceptive, neuropathic, or mixed? Answer: Nociceptive.Knowing what type of pain a patient is experiencing

is crucial for both identifying its likely source and de-termining the appropriate treatment. Nociceptive pain,which is caused by damage to somatic tissue (such asbones or muscle) or visceral tissue (such as the lungsor bladder), is treated differently from neuropathicpain, which is caused by damage to the peripheral orcentral nervous system. (See Table 1 for a comparisonof nociceptive and neuropathic pain.) Ms. Gordon de-scribes the pain as a deep ache in her knees; she denieshaving any burning, numbness, tingling, or shootingpain. Based on the character and location of Ms. Gor-don’s pain, the nurse determines that it’s nociceptive,caused by the osteoarthritis in her knees. The pain as-sessment algorithm next directs the nurse to an appro-priate pain management algorithm. In Ms. Gordon’scase, because she’s experiencing nociceptive pain thatshe rates as moderate to severe, the nurse is referredto the opioids algorithm shown in Figure 2.

Opioids algorithm. The opioids algorithm beginswith a box outlining criteria for its use: the patientmust be on an optimized acetaminophen (abbreviated

APAP) regimen and must have either moderate-to-severe pain (4 or greater on a 0-to-10 scale), pain that

The information gleaned from a thorough pain assessment will

help to determine the appropriate treatment regimen.


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Figure 2. Opioids Algorithm

APAP = acetaminophen; NSAIDs = nonsteroidal antiinflammatory agents.

Patient is optimized

on APAP

and has

Moderate-to-severe pain

(4 or greater on 0-to-10 scale)

and/or has

Pain that impairs function

Is the pain

localized

and affecting

superficial

structures?

Is the patient

currently

taking

opioids?

Has the

patient been

tried on topical

analgesics?

Yes

Yes

Yes

Yes

Yes

No

No

No

No

No

Initiate a short-acting

opioid at starting dose

Reassess after each

dose

Go to the NSAIDs

Algorithm

Initiate nondrug

strategies

Does

the patient

have persistent,unacceptable

adverse effects?

Go to the Opioids

Upward Titration

Algorithm

Conduct pain pattern

assessment; switch to

a long-acting opioid

for constant pain

Reassessas

appropriate

Is pain

controlled?

Initiate a trial

of capsaicin or

NSAIDs cream or

gel, or lidocaine

patch, and

reassess


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Does the patient have persistent, unacceptable ad-verse effects? Answer: No.

The algorithm recommends that after each dose ofa new opioid, the nurse reassess the patient’s pain leveland monitor for adverse effects. (The nurse would alsoconsult the separate algorithm for preventing and managing adverse effects of pain medications, not shownin this article.) In this case, knowing that constipationis a common adverse effect with opioids, the nurse alsorequests an order for a stool softener and a stimulantlaxative. During the initial 72 hours, Ms. Gordon takesoxycodone 2.5 mg each morning upon awakening,when her pain is worst, and every four to six hoursas needed thereafter. She experiences mild drowsinesswith the first dose of oxycodone but not with subse-quent doses. The nurse administers the stool softenerand laxative as ordered also, and Ms. Gordon main-tains her usual daily bowel movement.

Is the pain controlled? Answer: No.Successful pain management involves finding an

analgesia regimen that delivers maximum pain reliefwith minimal adverse effects. In some cases, a drug’sadverse effects such as nausea and vomiting may be

immediate and severe, and the drug may have to bestopped before the team can determine its effective-ness in relieving pain. In other cases, adverse effectsmay be milder and can be managed, allowing suffi-cient opportunity for the team to make that determi-nation.

On the third day of the new regimen, the nurseagain reviews the intensity and pattern of Ms. Gordon’spain. Ms. Gordon has indicated that on this regimenher usual pain has decreased—she rates it at 3 on the0-to-10 scale—but her morning pain remains mod-erate to severe. Thus her pain is fairly constant over-all but tends to worsen in the morning. This pattern isgenerally best managed with round-the-clock dosingwith a short-acting opioid for constant pain, plus anadditional dose for episodes of worsened pain. Be-cause the exacerbation occurs regularly and predict-ably, the additional dose should be scheduled (ratherthan taken as needed).

The nurse faxes the physician the updated pain as-sessment along with suggested changes to the regimen.Together they consult the opioids upward titrationalgorithm, which directs them to increase the dose by25% to 50%. They elect to schedule a 5-mg dose ofoxycodone once daily in the early morning, with sub-

sequent 2.5-mg doses at midday and at bedtime. Af-ter two days on this amended regimen, Ms. Gordon

Other contingencies might include a history of drugallergy or an earlier trial of a drug that resulted in intol- erable adverse effects or inadequate analgesia. In suchcircumstances, the nurse can ask the consulting phar-macist to investigate alternatives. In this case, she askswhether there is a similar topical medication on thepharmacy’s formulary, but none is found, and shemoves on to the next step of the algorithm.

Is the patient currently taking opioids? Answer: No. Since Ms. Gordon’s pain is moderate to severe and

she isn’t currently taking opioids, the algorithm ad-vises beginning with a short-acting opioid. Such use issuggested because short-acting opioids can be titratedfor pain relief more rapidly and safely than can long-acting opioids.30 The starting dose of a short-actingopioid may be less than the lowest available amountof a long-acting opioid, allowing more gradual titra-tion upward and lessening the likelihood of toxicity.

This is an especially important consideration in Ms.Gordon’s case, given her chronic renal failure. Also,short-acting opioids have shorter half-lives; shouldadverse effects occur, those associated with short-acting opioids can be managed more quickly than can

those associated with long-acting opioids.After completing a thorough assessment, to ensure

optimum communication, the nurse uses the Situation,Background, Assessment, and Recommendation Re-port to a Physician tool31 when consulting with Ms.Gordon’s physician. In describing the situation, thenurse reports that Ms. Gordon is experiencing worsen-ing and unrelieved pain in her knees. The nurse pro-vides background information, including Ms. Gordon’smedical history and current drug regimen, noting thather pain medications are no longer effectively reliev-ing her pain. The nurse also reports the pain assess-ment data and the algorithm’s recommendation toinitiate a short-acting opioid, to be taken as needed.Persistent pain in older adults is often undertreatedbecause of fears of oversedation, functional depen-dence, and addiction.32, 33 Anticipating that the physi-cian might be reluctant to prescribe an opioid for Ms.Gordon, the nurse explains the rationale for doing so,drawing on her knowledge of the literature. After con-sidering the relevant literature and discussing the prosand cons of opioid therapy with the nurse, the physi-cian orders oral oxycodone 2.5 mg every four to sixhours as needed, a dosage consistent with AGS guide-lines.5 The physician also requests that the nurse peri-

odically reevaluate Ms. Gordon’s pain level and ad-verse effects, and report back by fax in 72 hours.

While algorithms provide a logical approach to decision making,

they cannot replace critical thinking.


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Nociceptive Pain Neuropathic Pain

Definition Normal processing of stimulus that

damages normal tissue or has the

potential to do so if prolonged.

Abnormal processing of sensory input by

the peripheral or central nervous system.

Types Superficial somatic pain arises from

skin, mucous membranes, subcutane-

ous tissue; tends to be well localized.

Examples: sunburn, skin contusions

Deep somatic pain arises from mus-

cles, fasciae, bones, or tendons; local-

ized or diffuse and radiating.

Examples: arthritis, tendonitis, myofas-

cial pain

Visceral pain arises from visceral

organs, such as the GI tract or bladder;

well or poorly localized; often referred to

cutaneous sites.

Examples: appendicitis, pancreatitis,

cancer affecting internal organs

Central pain caused by primary lesion or

dysfunction in the central nervous system.

Examples: poststroke pain, pain associ-

ated with multiple sclerosis

Peripheral neuropathies felt along the

distribution of one or many peripheral

nerves; caused by damage to the nerve.

Examples: diabetic neuropathy, alcoholic

or nutritional polyneuropathy, trigeminal

neuralgia, postherpetic neuralgia

Deafferentation pain results from a loss

of afferent input.

Examples: phantom limb pain, postmas-

tectomy pain

Sympathetically maintained pain per-

sists secondary to sympathetic nervoussystem activity.

Examples: phantom limb pain, complex

regional pain syndromes

Character

(how pain is

typically

described)

Aching, throbbing, cramping, dull,

sharp, tender.

Shooting, electric-like, burning, stabbing,

pins and needles.

Treatment Usually responsive to nonopioid drugs,

opioid drugs, or both.

Usually includes adjuvant analgesics. For

example:

• topical agents such as capsaicin (Cap-

sagel and others), lidocaine (Lidoderm

and others)

• anticonvulsants such as gabapentin

(Neurontin), pregabalin (Lyrica)

• tricyclic antidepressants such as desi-

pramine (Norpramin), nortriptyline

(Pamelor, Aventyl)

• alternative antidepressants such as ven-

lafaxine (Effexor), bupropion (Wellbutrin

and others)

Table 1. Comparison of Nociceptive and Neuropathic Pain

GI = gastrointestinal.


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conclude that a trial of a short-acting opioid was theappropriate next step in achieving better pain relief.The opioids algorithm helped the nurse to further re-fine that trial. But it’s essential to remember that whilealgorithms provide a logical approach to decision making, they cannot replace critical thinking and individ-ualized patient care.

The illustrative case presented here is relatively un-complicated; in clinical practice, some cases will provemore complex. For instance, some patients might re-quire multiple trials of increasing doses of analgesicsor additional drugs for specific types of pain, such asneuropathic pain. Some patients may experience ad-verse effects from analgesia that will require assess-ment and management. (As noted earlier, for the NIHstudy we developed algorithms for many of these con-tingencies.)

Research indicates that nurses (and other clinicians)

often have inadequate knowledge about how to assesspain and about the medications used to treat pain.1, 33 In light of these knowledge deficits, algorithms areprobably best presented in a class or in-service trainingalong with resource materials that provide basic painassessment and management information. In the afore- mentioned NIH study, we tested the efficacy of a com-prehensive approach: nurses in both the control andintervention groups received education in pain assess-ment and management, but those in the interventiongroup also received instruction in the use of the algo-rithms and expert support; data analysis is still on-going. Another approach under investigation is the use

of Web-based versions of the algorithms, with embed-ded links to additional resources. Lastly, although ourfocus has been on the use of algorithms in pain assess-ment and management, nursing research aimed at de-veloping and testing the use of algorithms for otheraspects of patient care is also indicated.▼

Anita M. Jablonski is an associate professor at the Seattle Uni-versity College of Nursing. At the time of this writing, Anna R.DuPen was an advanced NP at the Hospice of Kitsap County,Bremerton, WA; currently she’s a palliative care NP at the Palli-ative Care Consultation Service in the Department of Family Med-icine at the University of Washington in Seattle. Mary Ersek isassociate director of the Center for Integrative Science in Agingand of the John A. Hartford Center of Geriatric Nursing Excel-lence, as well as an associate professor in the School of Nursing,at the University of Pennsylvania in Philadelphia. Previously shewas director of research at the Center for Nursing Excellence, aswell as a research scientist, at Swedish Medical Center in Seattle.Contact author: Anita M. Jablonski, [email protected]. Theresearch and development of the algorithms discussed herein weresupported by funding from the National Institutes of Health, Na-

tional Institute of Nursing Research (grant No. R01-NR009100).The authors of this article have disclosed no significant ties,

rates her usual pain at 3 and her morning pain at 2 or3. Although she reports feeling a bit sleepy after themorning dose, she doesn’t want to change it becauseit’s effectively relieving her pain. She adds that she’s de-lighted that she can again walk to breakfast.

The question Is the pain controlled? now yields ayes answer. At this point, the opioids algorithm indi-cates that a switch from a short-acting opioid to along-acting opioid might be warranted. There is evi-dence that older adults who require more than fourdoses of a short-acting opioid daily to manage con-stant pain might benefit from such a change. In a studyof more than 10,000 nursing home residents with per-sistent pain, long-acting opioids were found to be supe-rior to short-acting opioids in improving function andincreasing social engagement.34 Another study foundthat sleep quality improved when long-acting opi-oids were substituted for short-acting opioids.35 Use of

long-acting opioids may also improve adherence to thedosing schedule,36 as well as allowing patients to spendless time focusing on pain and pain management andmore time focusing on other aspects of their lives.36, 37

It’s unclear, however, whether long-acting opioidsare superior to short-acting opioids in relieving pain.30, 36 This aspect of pain management requires further study.Although both short-acting and long-acting opioidsplay important roles in pain management,30 criticalthinking and a thorough assessment of the pain pat-tern and the effects of pain on the patient’s quality oflife are crucial to evaluating which of the two types ofdrugs (or both) should be used.

Since Ms. Gordon is taking at least three doses ofthe short-acting opioid daily, the nurse discusses chang-ing to a long-acting opioid. Ms. Gordon is happy withthe pain relief she obtains on the current regimen andsays she doesn’t want to change medications at thistime. The nurse plans to reassess her pain pattern overthe next few days. If Ms. Gordon has breakthroughpain requiring additional doses of the short-acting opi-oid, the nurse may again suggest switching to a long-acting opioid.

FURTHER EDUCATION AND RESEARCH

The pain assessment algorithm that Ms. Gordon’snurse consulted guided the assessment and led her to

For 18 additional continuing nursing educa-tion articles on the topic of pain, go to www.nursingcenter.com/ce.

Resources

American Geriatrics Society

www.americangeriatrics.org

Free clinical practice guidelines.

American Medical Directors Association

www.amda.com

Clinical practice guidelines are available for a fee.

http://www.americangeriatrics.org/http://www.amda.com/http://www.amda.com/http://www.americangeriatrics.org/


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18. Hadorn DC. Use of algorithms in clinical guideline develop-ment. In: McCormick KA, et al, editors. Clinical practice

guideline development: methodology perspectives. Rockville,MD: Agency for Health Care Policy and Research; 1994.p. 93-104. http://www.acponline.org/clinical_information/ guidelines/process/algorithms/hadorn.pdf.

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