ceconnection for nursing
TRANSCRIPT
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.
[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 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.
[email protected] AJN ▼ March 2011 ▼ Vol. 111, No. 3 37
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.
[email protected] AJN ▼ March 2011 ▼ Vol. 111, No. 3 39
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
40 AJN ▼ March 2011 ▼ Vol. 111, No. 3 ajnonline.com
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.
[email protected] AJN ▼ March 2011 ▼ Vol. 111, No. 3 41
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.
42 AJN ▼ March 2011 ▼ Vol. 111, No. 3 ajnonline.com
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, [email protected]. 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.
[email protected] 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.
24. Melnyk BM, FineoutOverholt E. Consumer preferences and values as an integral key to evidencebased practice. Nurs Adm Q 2006;30(2):1237.
25. American Medical Directors Association. Clinical practice guideline: pain management. Columbia, MD; 2009. http://www.amda.com/tools/guidelines.cfm#chronicpain.
26. Agency for Healthcare Research and Quality, U.S. Depart ment of Health and Human Services. Choosing nonopioid analgesics for osteoarthritis: clinician summary guide. J Pain Palliat Care Pharmacother 2009;23(4):43357.
27. Heyneman CA, et al. Oral versus topical NSAIDs in rheumatic diseases: a comparison. Drugs 2000;60(3):55574.
28. McCleane G. Topical analgesic agents. Clin Geriatr Med 2008;24(2):299312, vii.
29. Lin J, et al. Efficacy of topical nonsteroidal antiinflammatory drugs in the treatment of osteoarthritis: metaanalysis of randomised controlled trials. BMJ 2004;329(7461):324.
30. Fine PG, et al. Longacting opioids and shortacting opioids: appropriate use in chronic pain management. Pain Med 2009;10 Suppl 2:S79S88.
31. Haig KM, et al. SBAR: a shared mental model for improving communication between clinicians. Jt Comm J Qual Patient Saf 2006;32(3):16775.
32. Kaasalainen S, et al. Pain management decision making among longterm care physicians and nurses. West J Nurs Res 2007;29(5):56180; discussion, 818.
33. Weiner DK, Rudy TE. Attitudinal barriers to effective treatment of persistent pain in nursing home residents. J Am Ger -iatr Soc 2002;50(12):203540.
34. Won A, et al. Longterm effects of analgesics in a popula tion of elderly nursing home residents with persistent nonmalignant pain. J Gerontol A Biol Sci Med Sci 2006;61(2):1659.
35. Caldwell JR, et al. Treatment of osteoarthritis pain with con trolled release oxycodone or fixed combination oxycodone plus acetaminophen added to nonsteroidal antiinflammatory drugs: a double blind, randomized, multicenter, placebo controlled trial. J Rheumatol 1999;26(4):8629.
36. Rauck RL. What is the case for prescribing longacting opioids over shortacting opioids for patients with chronic pain? A critical review. Pain Pract 2009;9(6):46879.
37. Vallerand AH. The use of longacting opioids in chronic pain management. Nurs Clin North Am 2003;38(3):43545.
financial or oth erwise, to any company that might have an inter-est in the publication of this educational activity.
REFERENCES 1. Fink R, Gates R. Pain assessment. In: Ferrell B, Coyle N,
editors. Textbook of palliative nursing. 2nd ed. New York: Oxford University Press; 2006. p. 97131.
2. National Center for Health Statistics. QuickStats: average life expectancy at birth, by race and sex—United States, 2000, 2006, and 2007. Hyattsville, MD: Centers for Disease Con trol and Prevention; 2009.
3. Xu J, et al. Deaths: preliminary data for 2007. Natl Vital Stat Rep 2009;58(1). http://www.cdc.gov/nchs/data/nvsr/nvsr58/nvsr58_01.pdf.
4. Centers for Disease Control and Prevention and the Merck Company Foundation. The state of aging and health in Amer ica 2007. Whitehouse Station, NJ: The Merck Company Foun dation; 2007. http://www.cdc.gov/Aging/pdf/saha_2007.pdf.
5. American Geriatrics Society, Panel on Pharmacological Man agement of Persistent Pain in Older Persons. Pharmacological management of persistent pain in older persons. J Am Geriatr Soc 2009;57(8):133146.
6. McCarthy LH, et al. Chronic pain and obesity in elderly peo ple: results from the Einstein aging study. J Am Geriatr Soc 2009;57(1):1159.
7. Won AB, et al. Persistent nonmalignant pain and analgesic prescribing patterns in elderly nursing home residents. J Am Geriatr Soc 2004;52(6):86774.
8. Zhang Y, et al. Prevalence of symptomatic hand osteoarthritis and its impact on functional status among the elderly: the Framingham Study. Am J Epidemiol 2002;156(11):10217.
9. Weiner DK, et al. How does low back pain impact physical function in independent, wellfunctioning older adults? Evi dence from the Health ABC Cohort and implications for the future. Pain Med 2003;4(4):31120.
10. Dawson J, et al. Epidemiology of hip and knee pain and its impact on overall health status in older adults. Rheumatology (Oxford) 2004;43(4):497504.
11. Jinks C, et al. Osteoarthritis as a public health problem: the impact of developing knee pain on physical function in adults living in the community: (KNEST 3). Rheumatology (Oxford) 2007;46(5):87781.
12. Onder G, et al. Association between daily pain and physi cal function among oldold adults living in the community: re sults from the ilSIRENTE study. Pain 2006;121(12):539.
13. Leveille SG, et al. Chronic musculoskeletal pain and the oc currence of falls in an older population. JAMA 2009;302(20):221421.
14. Gorina Y, et al. Trends in causes of death among older per-sons in the United States. Hyattsville, MD: National Center for Health Statistics, Centers for Disease Control and Preven tion; 2006. Aging trends, no. 6; http://www.cdc.gov/nchs/data/ahcd/agingtrends/06olderpersons.pdf.
15. World Health Organization. Physical activity and older adults: recommended levels of physical activity for adults aged 65 and above. n.d. http://www.who.int/dietphysicalactivity/factsheet_olderadults/en/index.html.
16. Institute of Medicine, Committee on the Future Health Care Workforce for Older Americans. Retooling for an aging Amer ica: building the health care workforce. Washington, DC: National Academies Press; 2008. http://books.nap.edu/ catalog.php?record_id=12089.
17. McConnell ES, et al. Teaching evidencebased nursing practice in geriatric care settings: the geriatric nursing innovations through education institute. J Gerontol Nurs 2009;35(4):2633.