JAMDA
Volume 10, Issue 1 , Pages 56-61, January 2009

Acute Myocardial Infarction in Nursing Home Residents: Adherence to Treatment Guidelines Reduces Mortality, But Why Is Adherence So Low?

  • Cari R. Levy, MD

      Affiliations

    • VA Eastern Colorado Healthcare System, HSR&D TREP for Long-term Care Research, Denver, CO
    • University of Colorado, School of Medicine Division of Health Care Policy and Research, Aurora, CO
    • Corresponding Author InformationAddress correspondence to Cari Levy, MD, VA Eastern Colorado Healthcare System, HSR&D TREP for Long-term Care Research, 1055 Clermont Street, Building C, Mailstop 151, Denver, CO 80220
  • ,
  • Tiffany A. Radcliff, PhD

      Affiliations

    • VA Eastern Colorado Healthcare System, HSR&D TREP for Long-term Care Research, Denver, CO
    • University of Colorado, School of Medicine Division of Health Care Policy and Research, Aurora, CO
  • ,
  • Elizabeth T. Williams, MS

      Affiliations

    • VA Eastern Colorado Healthcare System, HSR&D TREP for Long-term Care Research, Denver, CO
  • ,
  • Evelyn Hutt, MD

      Affiliations

    • VA Eastern Colorado Healthcare System, HSR&D TREP for Long-term Care Research, Denver, CO
    • University of Colorado, School of Medicine Division of Health Care Policy and Research, Aurora, CO

published online 11 December 2008.

Article Outline

Objectives

To investigate the applicability of clinical practice guidelines (CPGs) to the care of nursing home (NH) residents who experience acute myocardial infarction (AMI).

Design

Secondary examination of data from the national Cooperative Cardiovascular Project.

Setting

6684 US hospitals.

Participants

A NH-dwelling (N = 8151) cohort and a community-dwelling cohort (N = 119,012).

Measurements

Adherence to AMI guidelines and associated mortality rates.

Results

Mortality at 30 days and 1 year respectively was 39.5% and 65.4% in the NH cohort versus 17.5% and 31.1% in the community-dwelling cohort (P < .001). Among patients who were ideally eligible to receive aspirin, 58.8% of the NH cohort and 78.9% of the community-dwelling cohort actually received aspirin (P < .001). Among patients who were ideally eligible for beta-blockers, 43.8% of the NH cohort and 61.4% of the community-dwelling cohort received beta-blockers (P < .001). The 30-day mortality for NH patients who were ideally eligible for aspirin but did not receive aspirin was significantly higher compared with NH patients who were ideally eligible but did receive aspirin (49.2% versus 26.0%, P < .001). Similarly, mortality was significantly higher for NH patients who were ideally eligible for beta-blockers but did not receive a beta-blocker (35.3% versus 18.6%, P < .001).

Conclusion

Only half of NH patients who are ideally eligible for aspirin and beta-blockers received these medications, yet mortality was significantly lower in patients who were treated with these medications. These results demonstrate the effect of applying AMI guidelines to NH patients while also raising the question of what factors guided decisions not to provide these medications.

Keywords: Nursing home, clinical practice guidelines, geriatrics, acute myocardial infarction

 

The aging of the US population and increasing prevalence of chronic disease pose challenges to comprehensive application of clinical practice guidelines. Clinical practice guidelines (CPGs) are based on clinical evidence and expert consensus to guide decision making about treatment of specific diseases.1 CPGs are used to define and measure quality and performance.2 However, the safety of applying CPGs to the care of frail older adults has been questioned, because CPGs are generally derived from studies on younger healthier persons who meet strict eligibility criteria for participation in trials.3, 4 Specifically, care guidelines and quality metrics are needed for older persons residing in nursing homes where the average age is 84 years.5, 6

Research indicates that adherence to published coronary artery disease guidelines is suboptimal, particularly among minorities and the poor,7 for women,8, 9 and for those with care limitation orders in place,10, 11 but research has not examined whether care processes also differ based on source of admission from a nursing home (NH).12 Understanding how outcomes among patients transferred from NHs are affected by guideline adherence is important for several reasons. Forty-three percent of all Americans currently over age 65 will stay in an NH at least once during their lifetime.13 Second, the applicability of CPGs to frail, older adults with multiple comorbidities has not been established. Third, there is an increasing emphasis on establishing pay-for-performance measures based on achieving improved outcomes, but outcome measures associated with guideline adherence in this sub-population have not yet been established.

In a prior investigation we demonstrated that guidelines for treating acute myocardial infarction (AMI) were followed less consistently for patients with orders to forego life-sustaining interventions (eg, do not resuscitate, do not intubate orders).10 This study added to a body of literature suggesting that physician beliefs about patients may guide their decisions to offer certain treatments irrespective of evidence-based treatment guidelines.14, 15 In the current study, we hypothesize that guideline adherence may also be poor for patients transferred from NHs, and that lower guideline adherence would adversely impact mortality.

The main objective of this study was to investigate the applicability of treatment guidelines to the care of individuals living in NHs who experience an AMI. We have a unique national dataset that allows us to determine whether NH patients are treated differently than others admitted for acute myocardial infarction (AMI) while controlling for clinical eligibility for AMI treatments. These data also allow for comparison of outcomes between patients treated in accordance with guidelines and those for whom care was not provided in accordance with AMI treatment guidelines.

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Methods 

The primary data source for this research was the Cooperative Cardiovascular Project (CCP) national baseline data. The CCP was sponsored by the Centers for Medicare and Medicaid Services (CMS) to improve care provided to Medicare patients hospitalized with acute myocardial infarction. Chart abstraction of medical records was performed for a national cohort of fee-for-service patients with acute myocardial infarction under the authority of Medicare's Quality Improvement Organizations (QIOs) in order to measure guideline adherence rates and report these measures back to each admitting hospital. Information related to directives, care quality, and clinical eligibility was extracted from medical records by trained personnel at 2 clinical data abstraction centers. Data quality monitoring involved random re-abstraction of records with double entry of the information to ensure consistency across personnel, and data were found to be very reliable. Details regarding data collection procedures and main results of studies based on the data are available elsewhere.16, 17, 18, 19, 20, 21

The CCP national baseline data included an initial sample of 234,754 records abstracted from inpatient medical charts for fee-for-services Medicare beneficiaries hospitalized in 1 of 6684 hospitals located in any of the 50 states, the District of Columbia, or US territories between February 1994 and July 1995. Records were initially identified through inpatient hospital claims based on an International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) principal discharge diagnosis of 410 (acute myocardial infarction).22 We linked each record in the CCP data with information contained in the Medicare Denominator File, Area Resource File (ARF), and Medicare PPS cost reports for hospitals (PPS).

The final sample for this study included 127,163 cases. We excluded cases without a confirmed acute myocardial infarction diagnosis using criteria established by Marciniak and colleagues.21 We included only cases that were clearly admitted from either a long-term care or a community setting, as described later in this article. We also excluded cases with missing geographic information to allow us to control for local practice variation23, 24, 25; cases that were seen in nonacute facilities or with inadequate information to link with provider data; and cases that originated in states selected for the CCP pilot study due to differences in record abstraction timing and some of the measures. For individual treatment analyses, we excluded cases that were not deemed clinically eligible for the acute myocardial infarction treatments of interest using the criteria established by CMS and used in other research.17, 18, 20, 26, 27, 28, 29 Human subject's approval was received from the authors' local Institutional Review Board. Because data were collected prior to the implementation of HIPAA, consent was not required for this study; however, appropriate precautions to de-identify the data were taken.

To test whether admission from a long-term care setting was negatively associated with guideline adherence and if the relationship varied according to the intensity of the treatment, we examined several guidelines related to care during the hospital stay: (1) early administration of aspirin during the hospital stay, (2) early administration of beta-blockers during the hospital stay, and (3) reperfusion via either thrombolysis or angioplasty.

Guideline adherence and clinical eligibility indicators for the CCP data have been described extensively elsewhere.18, 20, 21, 28, 30, 31 Using previously established criteria for the CCP, we divided patients into eligibility groups, including ideal candidates, eligible candidates, and candidates for whom the care was contraindicated.21 For the present research, we included only patients who were ideally eligible for the treatment of interest. For aspirin, ideal candidates should not have had a gastrointestinal (GI) ulcer, same-day admission/discharge, history of bleeding disorder, risk of bleeding, anemia, allergy to aspirin, warfarin, or terminal illness. For beta-blockers, ideal candidates would have met the additional criteria of no evidence of congestive heart failure (CHF) (Killip <3), no insulin prior to admission, no hypotension, pulse greater than 50, no evidence of chronic obstructive pulmonary disease (COPD), no electrocardiogram (ECG) evidence of right bundle branch block (RBBB), left fascicular block, or second or third degree heart block. Candidates for reperfusion via percutaneous transluminal coronary angioplasty (PTCA) or thrombolysis must have had a confirmed AMI and not have been received in transfer from another hospital or emergency department. Ideal eligibility for reperfusion also required that the patient be under 80 years old, arrive at the hospital within 6 hours of symptom onset, show evidence of a transmural MI, not be taking warfarin, not having cardiac arrest requiring cardiopulmonary resuscitation (CPR), cardioversion, defibrillation, or chemical cardioversion in the 6 hours prior, not refuse a thrombolytic, not have received cardiac catheterization within 12 hours of arrival without PTCA, have no evidence of hepatic failure or cirrhosis, and have no history of active ulcer disease, internal bleeding, trauma, or injury in the month prior to arrival, and no bleeding risk, cerebral vascular accident, or surgery/biopsy within 2 months of admission.

The main variable of interest was pre-arrival setting, which was derived as part of the chart abstraction process. From the original 11 possible categories, we derived a single variable that indicates long-term care versus community setting prior to arrival. We defined a long-term care (LTC) setting to include patients admitted from a Skilled Nursing Facility (SNF) or Intermediate Care Facility (ICF), or chronic hospital. The LTC sample represents approximately 7% of the cases in our dataset. The comparison group included patients admitted directly from home or outpatient settings.

The analytic approach included a bivariate descriptive analysis comparing patients according to admission source. All analyses were performed using the Stata statistical package, version 9.2 SE (StataCorp, Stata Statistical Software: Release 9.2 SE, College Station, TX, 2006).

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Results 

Of the 127,163 patients in the analytic sample, 7.6% (n = 8151) were transferred from nursing homes for AMI care (see Table 1). The nursing home cohort was older on average than the community-dwelling cohort (82.6 versus 76.6 years, P < .001) and more likely to be female (69.1% versus 48.0%, P < .001). Do not resuscitate orders were written for 55.4% of the nursing home cohort compared to only 17.9% of the community-dwelling cohort (P < .001). Severity of illness scores were higher among the nursing home cohort with Acute Physiology and Chronic Health Evalution (APACHE III) scores of 50.8 in the nursing home cohort versus 37.6 in the community-dwelling cohort (P < .001). The nursing home cohort also had greater functional impairment (P < .001) and lower body mass index (P < .001). Mortality at 30 days and 1 year respectively was 39.5% and 65.4% in the NH cohort versus 18.9% and 33.4% in the community-dwelling cohort (P < .001).

Table 1. Characteristics of Sample Admitted for Acute Myocardial Infarction from Nursing Homes and the Community
Sample CharacteristicsOverallAdmitted from Nursing HomeAdmitted from Community
Number of cases127,1638,151119,012
Percentage of sample1007.6093.59
Average age, mean ± SD76.59±7.3782.64±7.6076.18±7.17
Female, %49.369.148.0
Non-white, %9.79.19.8
Length of stay, mean ± SD7.28±7.167.37±7.057.27±7.17
With DNR, %17.955.415.3
APACHE III, mean ± SD37.59±17.4650.80±20.9736.69±16.80
Charlson, mean ± SD2.22±1.222.71±1.302.19±1.20
BMI, mean ± SD26.17±5.2424.21±5.8926.27±5.18
FTE medical residents, mean ± SD29.40±78.5329.04±78.7129.43±78.45
FTE cardiologists, mean ± SD11.34±13.5111.02±13.8811.36±13.48
30-day mortality, %18.939.517.5
1-year mortality, %33.465.431.2

Sample inclusive from February 1994 to July 1995.

BMI, body mass index; DNR, do not resuscitate; FTE, full-time equivalent; APACHE III, Acute Physiology and Chronic Health Evaluation.

P ≤ .05

P ≤ .001.

Among patients who were ideally eligible to receive aspirin, 68.7% of the NH cohort and 85.9% of the community-dwelling cohort actually received aspirin (P < .001) (see Table 2). Among patients who were ideally eligible for beta-blockers, 43.8% of the NH cohort and 61.5% of the community-dwelling cohort received beta-blockers (P < .001). Only 30.4% of nursing home patients who were ideally eligible to receive reperfusion underwent reperfusion in contrast to 60.7% of the community-dwelling cohort (P < .001).

Table 2. Acute Myocardial Infarction Guideline Adherence for “Ideally Eligible” Patients by Admission Status from Nursing Home and Community
GuidelineOverall Study SampleAdmitted from Nursing Home (NH)Admitted from Community (C)Difference (NH − C)
Ideally Eligible for:Sample Size, n% AdherenceSample Size, n% AdherenceSample Size, n% Adherence% Difference
Aspirin82,38485.0437068.778,01485.9−17.2
Beta blocker35,05660.8121443.833,84261.5−17.6
Reperfusion16,77060.321430.416,50660.7−30.3

P < .001.

Among the NH patients who were ideally eligible for aspirin, the 30-day mortality significantly higher for those who did not receive it compared to NH patients who did receive aspirin (49.2% versus 26.0%, P < .001) (see Table 3). A similar pattern was observed for beta-blockers with mortality significantly higher for NH patients who were ideally eligible for but did not receive this treatment compared to NH patients who were ideally eligible but did receive this treatment (35.3% versus 18.6%, P < .001). Results for reperfusion were not statistically significant, which is partly attributable to the very small sample size of NH patients ideally eligible for reperfusion via either thrombolysis or PTCA.

Table 3. Mortality at 30 Days and 1 Year by Adherence to Acute Myocardial Infarction Guidelines for Patients Admitted from Nursing Homes
GuidelineNursing Home Study SampleSample Treated (T)Sample not Treated (NT)Difference (T − NT)
30-Day Mortality, %Sample Size, n30-Day Mortality, %Sample Size, n30-Day Mortality, %Sample Size, n%
Aspirin33.24,34726.02,99049.21,357−23.2
Beta blocker28.01,20918.653135.3678−16.6
Reperfusion27.421232.86425.01487.8
GuidelineNursing Home Study SampleSample Treated (T)Sample not Treated (NT)Difference (T − NT)
1-Year Mortality, %Sample Size, n1-Year Mortality, %Sample Size, n1-Year Mortality, %Sample Size, n%
Aspirin59.34,36852.93,00173.51,367−20.6
Beta blocker47.81,21438.453255.1682−16.8
Reperfusion48.621443.16551.0149−7.9

* P ≤ .05.

P ≤ .01.

P ≤ .001.

One-year mortality was also significantly higher in NH patients who did not receive aspirin or a beta-blocker despite meeting ideal eligibility criteria compared to NH patients who did receive these treatments when they met ideal eligibility criteria (aspirin 77.4% versus 56.9%; P < .001; beta-blockers 55.1% versus 38.4%, P < .001). Again, results for reperfusion were not statistically significant.

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Discussion 

This investigation has 3 important implications. First, the results indicate that adherence to AMI treatment guidelines improves outcomes among patients transferred from NHs. Second, the results provide evidence that would not preclude using AMI treatment guideline adherence as a pay-for-performance measure even for the NH population who are acutely hospitalized. Third, the results may raise concerns about disparities in care for NH patients with AMI.

It may be important to make a distinction between CPGs for chronic care and CPGs that apply to acute care.3, 4 The safety of applying CPGs to NH patients has been questioned, but in this investigation, the relative survival benefit of adherence to an acute care CPG for the treatment of AMI among patients transferred to acute care hospitals from NHs was greater than for community-dwelling patients. This investigation supports the utility of following AMI treatment guidelines even for frail populations such as those transferred from a NH.

The Medicare Payment Advisory Commission recommended that Medicare adopt pay for performance for physician reimbursement.32 As policy makers select performance measures, they will need to consider the validity and reliability of each measure when applied to the frail elderly population. Results from this investigation provide evidence that adherence to AMI treatment guidelines reduces mortality even in this unique population and suggests that AMI treatment guideline adherence could be considered as a pay-for-performance measure.

Discovering differences in AMI care that result in adverse outcomes is the first step toward reducing disparities in care. For example, after research demonstrated disparities in AMI care between men and women, programs were designed to improve care for women with AMI.21 Through the use of standardized orders and systems that reinforce the use of evidence-based AMI care, the Guidelines Applied in Practice (GAP) program has been shown to increase the use of evidence-based medicines at hospital arrival and discharge, smoking cessation counseling, and dietary counseling with reduction in mortality at 30 days and 1 year post-AMI.33

Our analysis focused on treatments where ideal eligibility was easily identified for both groups being compared. For angiotensin-converting enzyme (ACE) inhibitors, the sample size of ideal candidates was inadequately powered to detect a statistical difference between groups. Several other treatments were considered in the analysis, but the eligibility criteria were less clearly defined within the dataset. For example, thrombolytic therapy or PTCA were included as options for reperfusion. We were able to measure ideal eligibility for reperfusion overall, but could not differentiate ideal candidates according to the specific intervention.

Since our analysis focused on patients who were ideally eligible for the treatments and patients who refused treatment were excluded from the study, poor eligibility and treatment refusal are inadequate explanations for the observed differences. More likely, physicians and care teams failed to apply treatment guidelines based on perceived risks and benefits of treatments. This study suggests that such practices are not supported by evidence. Physician education about the benefits of treatment in this population is warranted. Physician education about the high mortality rates in this population is also warranted. With 30-day mortality rates of 30% and 1-year mortality over 50%, a discussion about patient preferences for care in the event of clinical decline are essential if the patient's preferences are to be honored. While the enthusiasm for living wills has waned in recent years because studies have not supported the utility of living wills,34 few would argue that a discussion about treatment preferences in this patient population from nursing homes with AMI is a worthwhile pursuit. In fact, studies such as this one, may allow practitioners to direct their efforts in advance care planning to those at highest risk of mortality.

Some may argue that mortality is not the correct outcome to measure in this population because this measure only captures quantity of life after AMI care, rather than the quality of AMI care. In future studies, researchers should also include process measures to capture the occurrence of explicit discussions among families, patients, and clinicians regarding the risks and benefits of AMI treatments. Just as clinicians have discussions with patients and families about the risks and benefits of CPR and mechanical ventilation, the risks and benefits of administering aspirin, beta-blockers, and reperfusion therapy should be explicitly discussed before a decision is made not to offer these potentially life-prolonging therapies.

This study has limitations. When examining large data sets as here, it is important to acknowledge that not all statistically significant findings have a practical significance. The data were collected during 1995, and may not adequately reflect the current state of the art for AMI or other changes in the organization, financing, and delivery of care for AMI. Nevertheless, administration of aspirin and beta-blockers in the care for AMI has not changed in a manner that would alter compliance with guidelines in association with admission from a nursing home. In addition, more contemporary databases with cardiovascular outcomes do not include a variable regarding admission from a NH.35

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Conclusion 

While some investigators have argued that most CPGs offer little guidance to clinicians caring for older patients with multiple comorbidities, this investigation suggests otherwise for AMI treatment guidelines.3, 4 Only half of NH patients who were ideally eligible for aspirin and beta-blockers received these medications, yet 30-day and 1-year mortality was significantly lower in patients who were treated with these medications when clinically indicated. These results demonstrate the positive effect of applying AMI guidelines for aspirin and beta-blockers to NH patients.35

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References 

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 C.R.L. is funded by a Veterans Affairs Career Development Award. She has no other financial disclosures. T.A.R. receives salary support through the US Department of Veterans Affairs Health Services Research & Development Research Enhancement Award Program (HSRD REA 06–0173) at the Denver VA Medical Center. She has no other financial disclosures. E.T.W. receives salary support through the US Department of Veterans Affairs Health Services Research & Development Research Enhancement Award Program (HSRD REA 06–0173) at the Denver VA Medical Center. She has no other financial disclosures. E.H. receives salary support through the US Department of Veterans Affairs Health Services Research & Development Research Enhancement Award Program (HSRD REA 06–0173) at the Denver VA Medical Center. She has no other financial disclosures.

 Data were provided by StratisHealth, the Quality Improvement Organization for Minnesota, the Centers for Medicare and Medicaid Services, and the University of Minnesota, Twin Cities.

 The analyses using Cooperative Cardiovascular Project (CCP) baseline data were performed under a Centers for Medicare & Medicaid Services Dissertation Fellowship Grant (No. 30-P-91016/5–01) awarded in 1999, which was extended through a data use agreement until 12/31/2009. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government. The authors assume full responsibility for the accuracy and completeness of the ideas presented. This article is the direct result of the Health Care Quality Improvement Program initiated by the Centers for Medicare and Medicaid Services, which has encouraged identification of quality improvement projects derived from the analysis patterns of care, and therefore required no special funding on the part of the contractor. Feedback to the authors concerning the issues presented is welcomed.

PII: S1525-8610(08)00275-2

doi:10.1016/j.jamda.2008.08.009

JAMDA
Volume 10, Issue 1 , Pages 56-61, January 2009