It’s no secret that greater numbers of Americans are living 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 numbers of such patients. Yet experts acknowledge that pain in older adults often goes underrecognized and under­treated.1 Algorithms—step­by­step guides—for pain assessment and management might help nurses and other clinicians begin to change this situation.

Over the last 50 years, the average life expect ancy for a U.S. citizen has increased from 69.7 to 77.9 years, according to the Centers for Disease Control and Pre­vention.2, 3 The proportion of citizens ages 65 years and older is also rising; experts predict that by 2030, older adults will constitute 20% of the population—about 71 million people.4 Moreover, about 80% of older Amer icans are now living with at least one chronic ill ­ness.4 For older adults, the persistent pain often asso­ciated with chronic illnesses is of particular concern because of its detrimental effects on functioning and quality of life.

Research indicates that there is a high prevalence of persistent pain among both community­dwelling older adults and nursing home residents.5­7 Pain associ­ ated with osteoarthritis of the hand,8 back,9 and hip and knee joints10, 11 plays a major role in significant func ­tional decline in older adults. A study in people ages 80 and older who reported daily pain from various conditions found that, as pain severity increased, mus­cle strength and physical performance progressively de clined.12 Another recent study found that older adults who have persistent pain are at increased risk for falls; the association held even after researchers adjusted for 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 ill­nesses can have detrimental effects on patients’ functioning and quality of life. Algorithms developed from evidence­based clinical practice guide lines are tools that can facili ­tate the application of research to practice. This article introduces readers to the use of algorithms in guiding the assessment and man­agement of persistent pain in older adults, and provides an illustrative case study.

Keywords: algorithm, clinical decision making, clinical practice guidelines, evidence­based practice, nursing judgment, older adults, pain

hours

Continuing Education2.9

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 AdultsAn introduction to tools that can facilitate the application of research to practice.

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Figure 1. Pain Assessment Algorithm

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

Go to the PainAssessment in

NonverbalPatient Algorithm

Treat theetiology as well

as the pain

Conduct paincharacter

assessment

Is the pain aresult of a

treatable etiology(such as a

UTI)?If pain is

NOCICEPTIVE

If pain isMIXED

If pain isNEUROPATHIC

Conductinitial painassessment

Is the patientcurrently

(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 patientgive self-report?

Reassessas

appropriate

Doestreatmentresolve

the pain?

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

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

Since nurses spend more time caring for older adults, in both community and residential settings, than do other health care professionals, they can be piv otal in ensuring that their patients’ pain is effectively assessed and managed. A nurse’s success in doing so will depend on various factors, including her or his comprehensive assessment skills; knowledge of ap ­pro priate, evidence­based treatment strategies; and decision­making ability. But basic nursing programs of ten don’t adequately prepare nurses to care for older adults or train them in how to apply best evidence to practice.16, 17

Algorithms developed from evidence­based clini­cal practice guidelines such as those published by the American Geriatrics Society (AGS) and the American Medical Directors Association (AMDA) are tools that can support and enhance nurses’ efforts to assess and manage persistent pain in older adults. Although al ­gorithms are frequently used by both physicians and nurses 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 what algorithms are and outlines their advantages and po ­tential drawbacks when used in clinical practice. Two algorithms that focus on pain assessment and treat­ment with opioids are presented, along with an illus­trative case.

ALGORITHMS: AN OVERVIEWClinical practice guidelines are derived from rigor ous systematic reviews of the current literature; they syn­thesize scientific evidence and expert opinion into rec­ommendations for best practice. But it may not be im ­mediately clear to a practitioner how to best implement those recommendations. Algorithms offer clinicians a method for doing just that.

An algorithm is a formula or set of rules for solving a problem, according to Taber’s Cyclopedic Medical Dictionary; Stedman’s Electronic Medical Dictionary defines the term as “a systematic process consisting of an ordered sequence of steps, each step depending on the outcome of the previous one.” An algorithm can guide the assessment or management of a given clinical problem, define the possible end points, and help the nurse to determine the best course of action. Typically an algorithm is presented as a flow diagram, with sev­eral branching pathways that lead to specified end points.18 For example, a nurse using the pain assessment

algorithm shown in Figure 1 will find a set of sequen­tial questions and instructions. Each ques tion can be answered “yes” or “no”; each answer di rects the user along a particular path and ultimately to a specific, rec­ommended action.

Advantages. Nurses make numerous decisions every day in clinical practice, the consequences of which directly affect outcomes of care. Because al go­rithms guide thinking in a logical, step­by­step ap ­proach, they can be used to refine nurses’ skills in de cision making, and can help to reveal gaps in a par­ticular assessment or management process, as well as er rors in thinking about a clinical problem.18, 20 Algo­rithms can be especially valuable for novice nurses who have less experience in decision making: they can help the nurse to make sound decisions and avoid flawed ones, thereby increasing her or his confidence.

Many nurses haven’t been adequately prepared to locate, interpret, and apply research findings and clini­cal guidelines to practice.21 Algorithms can be valuable teaching aids in addressing these deficits. Their visual, flow­diagram format has been shown to be effective in promoting learning and adherence to best prac­tice.18, 19, 22

Lastly, algorithms can reveal areas in which further research is needed. In an algorithm based on clinical practice guidelines, the recommendations made at var­ ious decision points will be supported by various levels of evidence. For example, the AGS’s guidelines for the pharmacologic management of persistent pain in older

adults advise that nonsteroidal antiinflammatory drugs (NSAIDs) be prescribed “rarely, and with ex treme cau­ tion, in highly selected individuals”; the recommenda­tion is based on strong, high­quality evidence such as that from randomized controlled tri als.5, 23 But sup­port for the use of nonpharmacologic methods (such as the application of heat or cold, acupuncture, and trans cutaneous electrical nerve stimulation) is much weaker, based on expert opinion or cli nicians’ expe­rience.23 An algorithm derived from these guidelines will reflect such differences in the strength and quality of evidence, thus underscoring gaps and weaknesses in the knowledge base.

Drawbacks and caveats. Critics have argued that algorithms are rigid and encourage robotic decision mak ing.18 Some contend that algorithms don’t take into account all possible factors, such as comorbidities, medical and social histories, and potential drug­drug interactions, that must be considered in making clin­ical decisions about treatment.18

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

skills in decision making.

But it’s not feasible to build all possible contingen­cies into an algorithm. An algorithm is designed to co ver the likely contingencies for the majority of pa ­tients with a given condition; still, individual differences must be considered. Moreover, to ensure high­quality care, patient preferences and values must also be in ­corporated into evidence­based practice.24

Finally, a given algorithm—like the practice guide­lines it’s based upon—can only be as strong as the un ­derlying evidence. Although many recommendations will have been validated with high­quality, strong em ­pirical evidence, others may necessarily be based on weaker evidence such as expert opinion. Thus, it’s im ­portant to emphasize that sound decision making isn’t a rote process; and that while algorithms can be excel­lent guides for clinical decision making, they cannot substitute for careful observation and critical thinking.

TWO ALGORITHMS FOR ADDRESSING PAIN IN OLDER ADULTS Two algorithms, one focusing on pain assessment and one on opioid therapy, are presented in Figures 1 and 2. They are from a series of algorithms developed for a study, funded by the National Institutes of Health (NIH), to evaluate the efficacy of algorithms in assess­ing and managing pain in older adults who reside in nursing homes. (All of us were involved in this study: ME was the primary investigator and AMJ and ARD were coinvestigators.) Each algorithm in the series ad ­dresses a major aspect of pain assessment and man­agement. There are separate algorithms for assessing pain in people who can and cannot self­report. There are also al gorithms to guide the use of specific types of analgesics (such as acetaminophen, NSAIDs, opioids, and adjuvant medications), as well as to guide assess­ment and management of analgesic­related adverse ef ­fects (such as constipation, sedation, and nausea and vomiting).

The algorithms are based on the relevant, evidence­based clinical practice guidelines developed by the AGS and the AMDA.5, 23, 25 A panel of experts in geri­atrics and pain reviewed the initial drafts, and the final drafts 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 in a reference manual and were tested during the interven­tion arm of the study. The study has been com pleted and data analysis is ongoing.

ILLUSTRATIVE CASEHelen Gordon, an 80­year­old resident in a long­ term care facility, suffers from several chronic illnesses, in cluding chronic renal failure; hypertension; osteo­porosis; and osteoarthritis, a progressive degenerative joint disease that affects several of the patient’s joints, particularly her knees. (This case is a composite based on our experience.) Until recently, she was able to walk using a walker. But during the past week, Ms. Gor­don 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 be most effective in helping Ms. Gordon to regain her previous level of independence. The first step toward managing her pain is a thorough pain assessment. The nurse refers to the algorithm shown in Figure 1 to guide the assessment, beginning with the oval shape in the upper left­hand corner.

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

As directed by the algorithm, the nurse first deter­mines that Ms. Gordon is alert and oriented and able to report her pain. The algorithm next instructs the nurse to conduct an initial pain assessment. If Ms. Gor don had been unable to self­report, the algorithm would have directed the nurse to use an algorithm de ­signed for patients unable to self­report.

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

The nurse’s assessment, which includes a physical examination and patient interview, reveals that Ms. Gordon is experiencing moderate­to­severe, nonradi ­ating, bilateral knee pain. Ms. Gordon reports that, until recently, this pain was mild to moderate and tol­erable; but during the past week it’s increased mark­edly. Asked to rate her current pain on a 0­to­10 scale, with 0 representing no pain and 10 representing the worst pain imaginable, Ms. Gordon rates her current pain at 6; she adds that it’s usually worse in the morn­ing, often at 7 or 8. The pain is exacerbated with ex ces­ sive movement and prolonged periods of immobility. Ms. Gordon is distressed by the adverse effect this pain is having on her ability to function independently; for example, she’s having difficulty showering and walk­ing to meals. She states that she’s depressed because the acetaminophen she’s been taking is no longer ef ­fectively relieving her pain.

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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

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

impairs function, or both. Ms. Gordon is already tak­ing up to 3 g of acetaminophen daily without satisfac­tory pain relief. She also rates her pain as greater than 4 and has decreased function because of pain. Thus the nurse determines that she may indeed require opi­oids to achieve effective pain relief, and continues to the next step of the opioids algorithm.

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

Superficial structures—structures relatively close to the body’s surface—could include skin, mucous mem­branes, subcutaneous tissue, and superficial tendons and ligaments. Ms. Gordon’s pain is nociceptive and localized in her knees, possibly as a result of increased inflammation around the joints.

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

Because Ms. Gordon’s pain is nociceptive and local­ized in her knee joints, it may respond well to topical analgesics, which haven’t yet been tried. The algorithm recommends that a trial of certain agents be initiated and the patient subsequently reassessed. The nurse ob ­tains an order for a trial of a topical NSAID, diclo­fenac so dium 1% gel, to be applied to both knees three times a day.

The strength of the evidence for some elements of the algorithm varies, as is the case here. Several top­ical agents can be used to treat pain, including lido­caine (Lidoderm and others), capsaicin (Capsagel and oth ers), and NSAIDs; topical preparations include creams, gels, and patches. In general, strong evidence supporting the use of topical analgesics, particularly for nonneuropathic pain, is lacking.5 But there is some evi­dence for the short­term efficacy of topical NSAIDs,26­28 although long­term efficacy hasn’t been established.29 Of the topical NSAIDs, preparations of di clo fenac and ibuprofen have been the most widely studied.26

The algorithm recommends an initial trial of a top ­ical analgesic because they tend to have fewer adverse effects and to interact less with other drugs than do sys­temic analgesics, making their use an advantage, es pe­ cially in elderly people, who are more likely to have multiple comorbidities for which they are receiving phar macotherapy.26, 28 More research is needed to clar­ify the proper role of these agents in managing pain.

An order for diclofenac gel is faxed to the institu­tion’s contract pharmacy; but this agent isn’t on the pharmacy’s preferred formulary, so the recommen ­dation cannot be acted on. This barrier points out the need 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 fallen or experienced other physical trauma in the last two weeks; Ms. Gordon says that she hasn’t. She also states that although the intensity of her pain seems to be worsening, its location and quality are unchanged. The findings of the nurse’s physical examination are consis­tent with Ms. Gordon’s known history, and a review of the medical record (X­ray reports, physician notes) re ­veals no evidence that Ms. Gordon’s pain results from a new or treatable source. The nurse concludes that the pain is probably the result of worsening osteoarthritis. Ms. Gordon receives medications for osteoporosis and restorative therapies (including physical therapy and massage) to slow the functional impact of osteoarthri­tis, but neither condition is curable.

As the algorithm indicates, the next step is for the nurse to further evaluate the character of Ms. Gordon’s pain. (See Basic Elements of Pain Assessment.) This step is crucial: the information gleaned from a system­atic and thorough pain assessment will help to deter­mine the appropriate treatment regimen, particularly with regard to analgesics.

Conduct pain character assessment: is the pain no ci- 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 as bones or muscle) or visceral tissue (such as the lungs or bladder), is treated differently from neuropathic pain, which is caused by damage to the peripheral or central nervous system. (See Table 1 for a comparison of nociceptive and neuropathic pain.) Ms. Gordon de ­scribes the pain as a deep ache in her knees; she denies having any burning, numbness, tingling, or shooting pain. Based on the character and location of Ms. Gor­don’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 appro­priate pain management algorithm. In Ms. Gordon’s case, because she’s experiencing nociceptive pain that she rates as moderate to severe, the nurse is referred to the opioids algorithm shown in Figure 2.

Opioids algorithm. The opioids algorithm begins with a box outlining criteria for its use: the patient must be on an optimized acetaminophen (abbrevi ated APAP) regimen and must have either moderate­to­ severe pain (4 or greater on a 0­to­10 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 optimizedon 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 patientcurrently

takingopioids?

Has thepatient been

tried on topicalanalgesics?

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 NSAIDsAlgorithm

Initiate nondrugstrategies

Doesthe patient

have persistent,unacceptable

adverse effects?

Go to the OpioidsUpward Titration

Algorithm

Conduct pain patternassessment; switch toa long-acting opioid

for constant pain

Reassess as

appropriate

Is paincontrolled?

Initiate a trialof capsaicin or

NSAIDs cream orgel, or lidocaine

patch, andreassess

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

The algorithm recommends that after each dose of a new opioid, the nurse reassess the patient’s pain le vel and monitor for adverse effects. (The nurse would also consult the separate algorithm for preventing and man­ aging adverse effects of pain medications, not shown in this article.) In this case, knowing that con stipation is a common adverse effect with opioids, the nurse also requests an order for a stool softener and a stimulant laxative. During the initial 72 hours, Ms. Gordon takes oxycodone 2.5 mg each morning upon awakening, when her pain is worst, and every four to six hours as needed thereafter. She experiences mild drowsiness with the first dose of oxycodone but not with subse­quent doses. The nurse administers the stool softener and laxative as ordered also, and Ms. Gordon main­tains her usual daily bowel movement.

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

an algesia regimen that delivers maximum pain relief with minimal adverse effects. In some cases, a drug’s adverse effects such as nausea and vomiting may be immediate and severe, and the drug may have to be stopped before the team can determine its effective­ness in relieving pain. In other cases, adverse effects may be milder and can be managed, allowing suffi­cient opportunity for the team to make that determi­nation.

On the third day of the new regimen, the nurse again reviews the intensity and pattern of Ms. Gordon’s pain. Ms. Gordon has indicated that on this regimen her usual pain has decreased—she rates it at 3 on the 0­to­10 scale—but her morning pain remains mod­erate to severe. Thus her pain is fairly constant over­all but tends to worsen in the morning. This pattern is generally best managed with round­the­clock dosing with a short­acting opioid for constant pain, plus an additional dose for episodes of worsened pain. Be ­cause the exacerbation occurs regularly and predict­ably, the additional dose should be scheduled (rather than 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 titration al gorithm, which directs them to increase the dose by 25% to 50%. They elect to schedule a 5­mg dose of oxycodone once daily in the early morning, with sub­sequent 2.5­mg doses at midday and at bedtime. Af ­ter two days on this amended regimen, Ms. Gordon

Other contingencies might include a history of drug al lergy or an earlier trial of a drug that resulted in intol­ er able adverse effects or inadequate analgesia. In such circumstances, the nurse can ask the consulting phar ­ma cist to investigate alternatives. In this case, she asks whether there is a similar topical medication on the pharmacy’s formulary, but none is found, and she moves 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 short­acting opioid. Such use is suggested because short­acting opioids can be ti trated for pain relief more rapidly and safely than can long­acting opioids.30 The starting dose of a short­acting opioid may be less than the lowest available amount of a long­acting opioid, allowing more gradual titra­tion upward and lessening the likelihood of toxicity.

This is an especially important considera tion in Ms. Gordon’s case, given her chronic renal failure. Also, short­acting opioids have shorter half­lives; should adverse effects occur, those associated with short­ acting opioids can be managed more quickly than can those associated with long­acting 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, the nurse reports that Ms. Gordon is experiencing worsen­ing and unrelieved pain in her knees. The nurse pro­vides background information, including Ms. Gordon’s medical history and current drug regimen, noting that her pain medications are no longer effectively reliev­ing her pain. The nurse also reports the pain assess­ment data and the algorithm’s recommendation to initiate a short­acting opioid, to be taken as needed. Persistent pain in older adults is often undertreated be cause of fears of oversedation, functional depen­dence, and ad diction.32, 33 Anticipating that the physi­cian 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 con­sidering the relevant literature and discussing the pros and cons of opioid therapy with the nurse, the physi­cian orders oral oxycodone 2.5 mg every four to six hours as needed, a dosage consistent with AGS guide­lines.5 The physician also requests that the nurse peri­odically 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, subcutane­ous tissue; tends to be well localized.

Examples: sunburn, skin contusions

Deep somatic pain—arises from mus­cles, fasciae, bones, or tendons; local­ized or diffuse and radiating.

Examples: arthritis, tendonitis, myofas­cial 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 associ­ated 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, postmas­tectomy pain

Sympathetically maintained pain—per­sists secondary to sympathetic nervous system activity.

Examples: phantom limb pain, complex regional pain syndromes

Character (how pain is typically described)

Aching, throbbing, cramping, dull, sharp, tender.

Shooting, electric­like, 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 desi­pramine (Norpramin), nortriptyline (Pamelor, Aventyl)

• alternative antidepressants such as ven­lafaxine (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 short­acting opioid was the ap propriate 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 while algorithms provide a logical approach to decision mak­ ing, they cannot replace critical thinking and individ­ualized patient care.

The illustrative case presented here is relatively un ­complicated; in clinical practice, some cases will prove more complex. For instance, some patients might re ­quire multiple trials of increasing doses of analgesics or additional drugs for specific types of pain, such as neu ropathic pain. Some patients may experience ad ­verse effects from analgesia that will require assess­ment and management. (As noted earlier, for the NIH study we developed algorithms for many of these con­tingencies.)

Research indicates that nurses (and other clinicians) often have inadequate knowledge about how to as sess pain and about the medications used to treat pain.1, 33 In light of these knowledge deficits, algorithms are pro bably best presented in a class or in­service training along with resource materials that provide basic pain as sessment and management information. In the afore­ mentioned NIH study, we tested the efficacy of a com­prehensive approach: nurses in both the control and intervention groups received education in pain as sess­ment and management, but those in the intervention group also received instruction in the use of the algo­rithms and expert support; data analysis is still on ­going. Another approach under investigation is the use of Web­based versions of the algorithms, with embed­ded links to additional resources. Lastly, although our focus has been on the use of algorithms in pain assess­ment and management, nursing research aimed at de ­veloping and testing the use of algorithms for other aspects 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 Pal li-ative Care Consultation Service in the Department of Family Med -icine at the University of Washington in Seattle. Mary Ersek is associate director of the Center for Integrative Science in Aging and 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 she was director of research at the Center for Nursing Excellence, as well as a research scientist, at Swedish Medical Center in Seattle. Contact author: Anita M. Jablonski, jablonsk@seattleu.edu. The research and development of the algorithms discussed herein were supported 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 or 3. Although she reports feeling a bit sleepy af ter the morning dose, she doesn’t want to change it because it’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 a yes answer. At this point, the opioids algorithm indi­cates that a switch from a short­acting opioid to a long­ acting opioid might be warranted. There is evi­dence that older adults who require more than four doses of a short­acting opioid daily to manage con­stant pain might benefit from such a change. In a study of more than 10,000 nursing home residents with per­sistent pain, long­acting opioids were found to be supe­rior to short­acting opioids in improving function and in creas ing social engagement.34 Another study found that sleep quality improved when long­acting opi ­oids were substituted for short­acting opioids.35 Use of long­ acting opioids may also improve adherence to the dosing schedule,36 as well as allowing patients to spend less time focusing on pain and pain management and more time focusing on other aspects of their lives.36, 37

It’s unclear, however, whether long­acting opioids are superior to short­acting opioids in relieving pain.30, 36 This aspect of pain management requires further study. Although both short­acting and long­acting opioids play important roles in pain management,30 critical thinking and a thorough assessment of the pain pat­tern and the effects of pain on the patient’s quality of life are crucial to evaluating which of the two types of drugs (or both) should be used.

Since Ms. Gordon is taking at least three doses of the short­acting opioid daily, the nurse discusses chang­ing to a long­acting opioid. Ms. Gordon is happy with the pain relief she obtains on the current regimen and says she doesn’t want to change medications at this time. The nurse plans to reassess her pain pattern over the next few days. If Ms. Gordon has breakthrough pain requiring additional doses of the short­acting opi­oid, the nurse may again suggest switching to a long­acting opioid.

FURTHER EDUCATION AND RESEARCHThe pain assessment algorithm that Ms. Gordon’s nurse 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 Societywww.americangeriatrics.orgFree clinical practice guidelines.

American Medical Directors Associationwww.amda.comClinical practice guidelines are available for a fee.

ajn@wolterskluwer.com AJN ▼ March 2011 ▼ Vol. 111, No. 3 43

18. Hadorn DC. Use of algorithms in clinical guideline develop­ment. In: McCormick KA, et al, editors. Clinical practice guideline development: methodology perspectives. Rockville, MD: Agency for Health Care Policy and Research; 1994. p. 93­104. http://www.acponline.org/clinical_information/guidelines/process/algorithms/hadorn.pdf.

19. Society for Medical Decision Making, Committee on Stan ­dardization of Clinical Algorithms. Proposal for clinical al ­gorithm standards. Society for Medical Decision Making Committee on Standardization of Clinical Algorithms. Med Decis Making 1992;12(2):149­54.

20. Siddall PJ, Middleton JW. A proposed algorithm for the man ­agement of pain following spinal cord injury. Spinal Cord 2006;44(2):67­77.

21. Pravikoff DS, et al. Readiness of U.S. nurses for evidence­based practice. Am J Nurs 2005;105(9):40­51.

22. Du Pen AR, et al. An educational implementation of a can­cer pain algorithm for ambulatory care. Pain Manag Nurs 2000;1(4):116­28.

23. American Geriatrics Society, Panel on Pharmacological Man ­agement of Persistent Pain in Older Persons. The manage­ment of persistent pain in older persons. J Am Geriatr Soc 2002;50(6 Suppl):S205­S224.

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