The Quality of Feeding Assistance Care Practices for Long-Term Care Veterans

Abstract

The primary purpose of this study was to determine the quality of feeding assistance care and identify areas in need of improvement for a sample of long-term care veterans. A secondary purpose was to compare these findings with the results of previous studies in community facilities to determine ways in which the VA sample might differ. A repeated measures observational study was conducted in two VA facilities with 200 long-stay residents. Research staff conducted standardized observations during and between meals for 3 months. There was a trend for better feeding assistance care quality during meals in the VA sample, but there were still multiple aspects of care in need of improvement both during and between meals. Higher licensed nurse staffing levels in the VA should enable effective supervision and management, but observation-based measures of care quality are necessary for accurate information about daily feeding assistance care provision.

Keywords

long-term care VA facilities quality of care nutrition feeding assessment

Introduction

The Veterans Administration (VA) health care system is one of the largest integrated systems in the United States and has been a leader in the implementation of numerous care quality initiatives. There are currently 132 VA Community Living Centers (CLCs) in the federal VA system and 175 state-sponsored VA facilities nationwide, both of which provide long-term care services analogous to community nursing homes. The staffing levels in VA facilities greatly exceed that of most community nursing homes. Specifically, total staffing for federal VA facilities is reported to be above 4.0 nursing hr per resident day, which places VA facilities in the 90th percentile for staffing relative to community facilities (Department of Veterans Affairs [VA], 2010; Harrington, Carillo, Blank, & O’Brian, 2010). Total staffing level has been shown to be a significant predictor of care quality in community facilities (Castle, 2008; Schnelle et al., 2004; Schnelle, Simmons, & Cretin, 2001). Thus it is reasonable to hypothesize that care quality may be better in the VA relative to community facilities due to higher overall staffing levels. However, there is sparse data to support this hypothesis. The purpose of this study was to describe the quality of feeding assistance in two VA facilities and compare these data to published data from community facilities using validated measures (Simmons, Babineau, Garcia, & Schnelle, 2002; Schnelle et al., 2009).

In addition to the availability of published data from community facilities for comparison, there are several other reasons to focus on the quality of feeding assistance in the VA. First, mealtime feeding assistance is labor intensive and represents a key daily care process to prevent unintentional weight loss (Simmons et al., 2008; Simmons & Schnelle, 2004). Moreover, feeding assistance care quality has been shown to be significantly related to staffing in community facilities (Kayser-Jones & Schell, 1997; Schnelle et al., 2001, 2004). Thus it is reasonable to expect that VA facilities might provide better feeding assistance care also, due to higher staffing levels. Second, there have been recent efforts to initiate cultural transformation in VA facilities nationwide, which consist of creating a more home-like, resident-centered care environment. These initiatives also emphasize resident choice as it relates to multiple aspects of daily care, including dining (Kheirbek, n.d.). Recent studies also have demonstrated that providing choice is important to increase residents’ food and fluid consumption and quality of life (Carrier, West, & Ouellet, 2009; Desai, Winter, Young, & Greenwood, 2007; Nieuwenhuizen,Weenan, Rigby, & Hetherington, 2010; Simmons & Schnelle, 2004; Simmons, Zhuo, & Keeler, 2010). In addition, new survey regulations include the availability of choice as it relates to dining (Center for Medicare and Medicaid Services [CMS], 2008). Finally, the results of previous studies also have indicated that nutritional care quality is in need of improvement in the VA, although there is a dearth of current studies about this issue (Abassi & Rudman, 1993; Liu, Bopp, Roberson, & Sullivan, 2002; Rudman et al., 1987; Sullivan, Bopp, & Roberson, 2002).

There have been no published studies to evaluate the quality of feeding assistance care provided to VA long-term care residents. A recent observational study in 10 community facilities revealed significant care quality problems across all 10 sites related to the accuracy of chart documentation and the adequacy and quality of mealtime feeding assistance (Simmons et al., 2002). Separate studies in community facilities also have shown that staff do not consistently offer residents choices during mealtime or provide additional foods and fluids between meals more than once per day, on average (Kayser-Jones et al., 1998; Schnelle et al., 2009; Simmons et al., 2010; Simmons & Patel, 2006; Simmons & Schnelle, 2004). However, community facilities with staffing above 3.8 have been shown to perform significantly better than facilities staffed below this level on multiple care quality indicators, including nutritional care quality (Schnelle et al., 2004).

The present study examined feeding assistance care quality both during and between meals for a sample of long-term care veterans using standardized observational protocols previously applied to community facilities (Schnelle et al., 2009; Simmons et al., 2002). The primary purpose of this study was to determine the quality of feeding assistance care and identify areas in need of improvement in the VA sample as part of a larger quality improvement effort. A secondary purpose was to compare these findings with the results of previous studies in community facilities to determine ways in which the VA sample might differ.

Method

Subjects and Setting

Participants were recruited from two VA facilities in one geographic region that housed a total of 282 residents at the time of the study (total bed size was 140 and 161 and occupancy rates were 87% and 99%, for Sites 1 and 2 respectively). Nurse-aide level staff-to-resident ratios, as reported by the Directors-of-Nursing, ranged from 8 to 9 residents per nurse aide during the day (7:00 a.m. to 3:00 p.m.), 9 to 10 on the evening (3:00 p.m. to 11:00 p.m.), and 14 to 15 on the night (11:00 p.m. to 7:00 a.m.) shifts and were comparable between the two VA sites across all three shifts. Licensed nurse (RN + LPN) staffing ratios at the two sites were 6 to 15 residents per licensed staff for the day, 12 to 15 for the evening, and 13 to 15 for the night shifts and were comparable between the two VA sites for the evening and night shifts but higher in Site 2 for the day shift, primarily due to a higher number of LPN staff. Both sites had a RN-level nurse manager for each unit within the facility (Site 1—3 units; Site 2—4 units). Relative to community facilities in previous studies, nurse aide staffing levels were comparable but licensed nurse staffing levels were higher for these two VA sites (Schnelle et al., 2004, 2009; Simmons et al., 2002; Simmons & Schnelle, 2004). The two VA study sites reported 3.82 (Site 1) and 5.0 (Site 2) total nursing hours per resident day, which placed both in the upper quartile of all homes in the nation (VA, 2010; Harrington et al., 2010; Schnelle et al., 2001).

A total of 270 (96%) residents met study inclusion criteria, which required residents to be long-stay (non-Medicare), free of a feeding tube, not receiving hospice, and not on a planned weight loss diet. Consent was obtained for 222 (82%) eligible residents. Study procedures were approved by the VA institutional review board. Following consent, 22 participants were lost from the study due to transferring out of the facility (n = 13) or incomplete data (n = 9). The remaining 200 participants comprised the study sample.

Measures

Descriptive information was retrieved from each participant’s medical record using a standardized form. Each participant’s most recent Minimum Data Set (MDS version 2.0) also was retrieved to calculate MDS-derived scale scores for cognitive and physical functioning (Health Care Financing Administration [HCFA], 1999; Hartmaier et al., 1995; Morris, Fries, & Morris, 1991). The Cognitive Performance Scale (CPS) score ranges from 0 (cognitively intact) to six (severely impaired) (Hartmaier et al., 1995). The Activities of Daily Living (ADL) scale score ranges from 0 (rated by staff as independent in each of 7 areas) to 28 (rated by staff as completely dependent in all areas) (Morris et al., 1991). Staff ratings of eating dependency (Section G. Physical functioning, item 1h) also were abstracted separately (score range 0 = completely independent to 4 = total dependence) (HCFA, 1999).

Mealtime Observations and Care Process Measures

Trained research staff used a standardized observation protocol shown to be reliable and valid in previous studies to conduct observations during regularly scheduled meals for a total of 12 meals per person across 2 consecutive months (6 meals per month; or, breakfast, lunch and dinner on 2 consecutive week days) under usual care conditions (Schnelle et al., 2009; Simmons et al., 2002, 2003; Simmons & Reuben, 2000). Continuous observations were conducted from the time of meal delivery until the time of meal retrieval (mean observation time = 80.55 ± 24.51 min per person per meal). Research staff documented all types of staff assistance provided during the meal to encourage intake including: setup (e.g., opening containers, cutting up meat), verbal reminders, physical help to eat, and staff offers of alternatives to the served meal. All episodes of assistance were combined to yield a total assistance time (minutes:seconds) per person per meal. In addition, research staff also recorded dining location (in room vs. dining room) and the type(s) of staff who provided assistance (i.e., nurse aides, licensed nurses) per person per observation period.

Research staff estimated total percent consumed (all foods and fluids combined) per person per meal based on observation because this is the method used by facility staff to document daily meal intake (Simmons et al., 2002, 2003; Simmons & Reuben, 2000). In addition, digital photographs were taken for at least one meal per person and rated by a trained staff member different from the observer for reliability. Both observation and photography methods have been shown to be reliable methods for estimating residents’ meal intake (Simmons & Reuben, 2000). The pearson correlation between the observation and photo-based estimates for total percent intake of meals was r = .94, p < .001 (n = 365 resident-meals) in this study.

Interrater reliability among research staff for each of the observation-based data elements (n = 155 resident meals) were as follows: meal delivery and retrieval times (r = .925, p < .001); total assistance time (r = .923, p < .001); total percent eaten (r = .987, p < .001); physical assistance to eat (κ = .946, p < .001); verbal reminders to eat (κ = .513. p < .001); and, alternatives offered (κ = .854 p < .001). These data elements were used to calculate care process measures shown to be reliable, valid measures of feeding assistance care quality (Schnelle et al., 2004, 2009; Simmons et al., 2002, 2003). Each measure is scored per person per meal because staff could provide assistance during breakfast but not lunch, for example. Each measure is scored as a “pass” or “fail” to yield an overall “percent pass rate” across all resident-meal observations, where a higher score translates into better care quality (Schnelle et al., 2004, 2009; Simmons et al., 2002, 2003). Each of the below care process measures has been specifically described in multiple previous studies (Schnelle et al., 2004, 2009; Simmons et al., 2002, 2003); thus only a brief description of the scoring rule and rationale is presented here.

Feeding Assistance Care Process Measures: Scoring Rules and Rationale

1. Staff ability to accurately identify residents with clinically significant low intake of meals.

Scoring Rule: Score as “fail” if a resident consumes less than 50% of his or her meal based on observation but staff documentation shows more than 60%. Only meals with intake below 50% are scored.

Rationale: If a resident consumes less than 75% of most meals, she or he meets the MDS criterion for low intake (HCFA, 1999). Evidence, however, suggests that residents who consume less than 50% of most meals are at a significantly higher risk for weight loss. Thus, if staff document more than 60% when the resident ate less than 50%, staff may fail to identify a clinically significant oral intake problem.

2. Staff ability to provide assistance to at-risk residents.

Scoring Rule: Score as “fail” if a resident consumes less than 50% of his or her meal based on observation and also receives 1 min or less of staff assistance. Only meals with intake below 50% are scored.

Rationale: If residents who consume less than 50% also receive 1 min or less of assistance, staff are providing potentially suboptimal feeding assistance, failing to recognize an oral intake problem or both. The 1-min criterion allows for meal delivery and retrieval only.

3. Staff ability to provide assistance to residents identified as requiring assistance to eat.

Scoring Rule: Score as “fail” if a resident is rated on their most recent MDS assessment as requiring feeding assistance (G1h rated 2-4: Limited, extensive, or total assistance) and receives less than 5 min of assistance from staff (HCFA, 1999).

Rationale: Staff should provide assistance to residents documented as requiring assistance to eat. A 5-min criterion is used because residents who are completely dependent on staff to eat are included in this group. Previous work has shown that a 5-min criterion reflects a meaningful cutoff such that residents whose assistance falls below 5 min receive, on average, only 1 to 2 min of tray setup, whereas those whose assistance is more than 5 min receive, on average, 10 to 15 min of total assistance (Simmons et al., 2002, 2003; Simmons & Schnelle, 2006b).

4. Staff ability to provide a verbal prompt to residents who receive physical assistance to eat.

Scoring Rule: Score as “fail” if a resident receives physical assistance to eat without also receiving at least one verbal prompt (e.g., “Try a bite of soup.”). Only meals during which staff provide physical assistance to eat are scored.

Rationale: Verbal prompting increases residents’ independent eating behaviors and meal intake. Staff often provide excessive physical assistance to residents who could otherwise eat independently with verbal prompting or encouragement (Kayser-Jones & Schell, 1997; Lange-Alberts & Shott, 1994; Simmons et al., 2003, 2008; Simmons & Schnelle, 2004, 2006b; Van Ort & Phillips, 1995).

5. Staff ability to offer an alternative to the served meal when a resident’s intake is low.

Scoring Rule: Score as “fail” if a resident consumes less than 50% of the served meal and is not offered an alternative by staff. Only meals with intake below 50% are scored.

Rationale: Federal guidelines specify that alternatives should be available for every meal (HCFA, 1999). Minimally, staff should notice when a resident is eating poorly and offer the resident an alternative (HCFA, 1999; Kheirbek, n.d). Staff receive a “pass” score for offering an alternative or any substitutions, even if the resident declines.

Between-Meal Observations

Continuous observations between meals were conducted on the same days as meal observations during the morning, afternoon, and evening (mean observation time = 91.34 ± 8.76 min per person per observation period). Thus each participant had a total of up to 12 between-meal observation periods across 4 days. Trained research staff documented staff offers of any food or fluid item, including supplements. The total amount of assistance provided by staff to encourage intake was documented between meals in the same manner as during meals.

Data Analyses

All characteristics shown in Table 1 were compared between study participants (n = 200) and those lost from the study (n = 22) using independent samples t test for continuous variables and chi-square analyses for categorical variables. There were no statistically significant differences. In addition, all characteristics shown in Table 1 were also compared between participants in site 1 (n = 63) and participants in Site 2 (n = 137). Participants with 6 or more observations were included in analysis (median and mode = 12 observations per person for both meal and between-meal periods). Because meals and between-meals were observed on the same days, there was comparable missing data for both (7% of total observations), with the most common reason being “out of the facility” at the time of observation.

Table 1.

Participant Characteristics Overall and by VA Study Site (n = 200).

	Overall (n = 200)	Site 1 (n = 63)	Site 2 (n = 137)
Measure	Percent (n) or Mean (± SD)	Percent (n) or Mean (± SD)	Percent (n) or Mean (± SD)
Percent male**	89% (177)	75% (48)	95% (130)
Percent White	87% (171)	92% (58)	85% (113)
Age in years**	76.00 (±11.97)	81.56 (±7.40)	73.44 (±12.80)
Length of Stay in Years**	3.23 (±2.56)	2.26 (±1.80)	3.70 (±2.73)
Percent with dementia diagnosis**	58% (115)	81% (51)	47% (64)
Percent with depression diagnosis*	42% (83)	57% (36)	35% (47)
MDS-CPS (0-6)**	2.29 (±1.75)	2.94 (1.44)	1.99 (1.81)
MDS-ADL (0-28)*	12.69 (±8.94)	15.54 (6.70)	11.36 (9.45)
MDS eating dependency (0-4)*	1.25 (±1.26)	1.65 (1.17)	1.06 (1.26)
Percent with MDS eating dependency rating 2-4 (limited to extensive assistance)	33.3% (66)	40% (25)	30% (41)
Percent with recent weight loss on MDS	11% (21)	8% (5)	12% (16)
Percent with prescribed diet order**	80% (159)	60% (38)	88% (121)
Percent with caloric supplementation order**	73% (146)	44% (28)	86% (118)
Percent with BMI < 21	15% (26)	16% (9)	14% (17)

Note: SD = standard deviation. MDS-CPS: Minimum Data Set derived Cognitive Performance Scale total score ranges from 0 (cognitively intact) to 6 (severely impaired or comatose). MDS-ADL: Minimum Data Set derived Activities of Daily Living total score range 0 (rated by staff as completely independent) to 28 (rated by staff as completely dependent in 7 ADLs). MDS eating dependency item (section G. physical functioning) ranges from 0 (independent) to 4 (totally dependent). Prescribed Diet Order: Any type of altered diet (no added salt, no concentrated sugars, mechanically altered, ground, puree). Caloric Supplementation Order: Physician or Dietitian order for oral liquid nutrition supplement or the provision of additional foods and fluids between meals. Body Mass Index (BMI) formula = 0.454 × weight in pounds/(0.254 × height in inches)²

p < .05. **p < .01.

The two VA sites were compared on each measure to determine potential site differences. Because data collection was conducted as part of a repeated measures design, observations for individual participants may exhibit serial correlation. To account for this, odds ratio (OR) estimates and corresponding 95% confidence intervals (CI) were constructed using a nonparametric cluster bootstrap technique (Van der Leeden, Meijer, & Busing, 2008). The odds associated with Site 1 measures were considered significantly different from Site 2 when the corresponding 95% confidence limits were both greater than one, or both less than one.

Results

Overall participants were predominately male and White, with an average age of 76 and an average length of residency of 3.2 years (Table 1—Overall). Participants were moderately cognitively impaired as evidence by Dementia diagnosis (58%) and MDS-CPS total score (2.3 ± 1.8). Forty-two percent had a diagnosis of depression. Participants were mildly to moderately physically impaired based on the MDS-ADL total score (12.7 ± 8.9), and 33% were rated by staff as requiring assistance to eat. The majority (80%) had a prescribed diet order and/or an order to receive caloric supplementation daily (73%). Eleven percent had a recent weight loss episode (MDS: > 5% in 30 days or > 10% in 180), and 15% had a Body Mass Index below 21, which is indicative of undernutrition (Fiaterone Singh & Rosenberg, 1999).

The two VA samples differed significantly on most of the characteristics shown in Table 1 (Site 1 and Site 2 columns). There was a greater proportion of male participants in VA Site 2 (χ² = 17.45, p < .001), and Site 2 participants were also significantly younger in age (t = −4.68, p < .001). Site 2 participants had been in the facility for a longer period of time (t = 3.80, p < .001). A smaller proportion of Site 2 participants had a dementia diagnosis (χ² = 20.27, p < .001) or a depression diagnosis (χ² = 9.03, p = .003) and were less cognitively (MDS-CPS, t = −3.65, p < .001) and physically impaired (MDS-ADL t = −3.13, p = .002; MDS eating dependency t = −3.15, p = .002) relative to Site 1 participants. Finally, a greater proportion of Site 2 participants had a prescribed diet order (χ² = 38.05, p < .001) or a caloric supplementation order (χ² = 17.45, p < .001).

Meal Delivery Care Practices

A significantly higher proportion of resident-meals in Site 1 were observed in the dining room (84.4% vs. 46.5%, OR = 0.16, CI = [0.084, 0.28]). A previous cross-sectional study in 34 community facilities showed that feeding assistance care quality was significantly better if a resident ate meals in the dining room compared to his or her room, after adjusting for resident characteristics and staffing level (Simmons & Levy-Storms, 2005). Site 1 also provided buffet style dining for the breakfast meal at least once per week, which was available to all residents, whereas Site 2 had a separate cafeteria where only ambulatory, independent residents were able to retrieve alternatives to the regularly served meal and/or snacks between meals. Site 2 had more licensed nurses assisting during mealtime, mostly LPNs, whereas Site 1 had additional staff beyond nurse aides (1 “hydration tech” per unit) who offered residents additional fluids between meals. Both sites had comparable meal service time periods (approximately 2 hr per meal).

Observation-Based Care Process Measures During Meals

Table 2 shows the percent “pass” rates for the observation-based care process measures during meals for the group of 200 VA participants overall and for each of the two sites (range). For comparison, the percent pass rates for these same care process measures in 10 community facilities (overall and range) are also shown in Table 2 based on the results of a previous study (Simmons et al., 2002).

Table 2.

Percent Pass Rates for Feeding Assistance Care Process Measures during Meals: VA and Community Facilities.

	2 VA facilities N = 200	10 community facilities N = 302
Care process measures	Percent pass rate (range)	Percent pass rate (range)
Observation showed < 50% total percent consumed	33% (32%-34%)	45% (40%-52%)
Observation showed < 50% total percent consumed and medical record documentation showed a value < 60%	54% (50%-61%)	38% (9%-76%)
Observation showed < 50% total percent consumed and > 1 min of staff assistance was provided	55% (49%-65%)^a	44% (27%-75%)
Medical record documentation that staff assistance to eat was needed	33% (31%-39%)	27% (17%-43%)
Medical record documentation that staff assistance to eat was needed and > 5 min of assistance was provided based on observation	53% (51%-57%)	44% (18%-89%)
Observation showed that physical assistance to eat was provided with at least one episode of verbal cueing	94% (92%-95%)	65% (0%-100%)

Note: Rates for community nursing home sample were previously reported as “percent fail” rates and were converted to “percent pass” rates for purpose of comparison in this study.

Significant difference between two VA sites.

The number of participant observations scored for each measure differed based on the scoring rule criteria (see Method). Overall, participants consumed less than 50% of the served meal during 33% (734 of 2,238) of the observations. Chart documentation showed a value < 60% for approximately half, or 53.7% (394 of 734), of these meals (Table 2, row 2). For these same low-intake meals, staff provided more than 1 min of assistance during 54.5% (400 of 734, Table 2, row 3), with a significant difference in the pass rates between the two VA sites (OR = 0.52; 95% CI = [0.30, 0.87]). Staff offered an alternative to the served meal during only 3% (21 of 734, not shown in Table 2) of these low-intake meals with, again, a significant difference between the two sites (0.2% vs. 8.4%, OR = 0.02; CI = [0.00, 0.09]).

Approximately one third of the participants were rated by staff as requiring feeding assistance (Table 2, row 4). Staff provided at least 5 min of assistance during 53.4% (399 of 747) of these meals (Table 2, row 5), with an average total assistance time of 11 (± 11) min per person per meal. For those who received physical assistance, staff also provided at least one episode of verbal cueing during 93.8% (441 of 470) of meals (Table 2, row 6).

Relative to the community sample (Table 2, column 2), these two VA sites had a smaller proportion of residents with low intake and consistently higher “pass rates” for the mealtime care process measures although there was a broad range of pass rates across the 10 community sites and a few significant differences between the two VA sites. The one exception to this trend for better mealtime care in the VA sample was staff offers of alternatives to the served meal when intake was low, which was below 10% in both VA sites. In contrast, a separate nationwide study conducted in 20 community facilities in 5 states showed that staff offered alternatives to the served meal 75% of the time for those who ate poorly based on observation (Schnelle et al., 2009).

Between-Meal Observations

Overall, participants were offered additional foods and fluids between meals on average 1.32 (± 0.65) times per person per day (range 0-3), or during 48% of the between-meal observations. This frequency was only slightly higher for those with a caloric supplementation order (1.43 ± 0.60). When snacks or supplements were offered between meals, staff provided an average of 2.4 (± 6.6) min of assistance per person per snack; and, total assistance time was not significantly greater for those rated by staff as requiring assistance to eat (mean = 3.2 ± 5.7 min). Separate studies in community facilities have shown similarly low rates of staff offers of additional foods and fluids between meals and little assistance to promote consumption, even for those with orders to receive caloric supplementation (Kayser-Jones et al., 1998; Simmons & Patel, 2006; Simmons et al., 2010; Simmons & Schnelle, 2004).

Discussion

This study used standardized observation-based measures previously applied in community facilities to examine the quality of feeding assistance care in two VA long-term care facilities. There are a few notable study limitations. This study included only two VA facilities in one geographic region with predominately White, male participants. Thus results may not be generalizable to a nationwide sample of VA facilities and/or VA facilities that house a larger proportion of female or minority residents. It should also be noted that VA long-term care residents in this study were, in general, characterized by a greater proportion of male residents, younger age, longer length of stay, and less physical and cognitive impairment relative to the community sample used for comparison (Simmons et al., 2002). These demographic and functional characteristic differences between VA and community long-term care residents are consistent with findings in other studies (Buchanan et al., 2004). Irrespective of these differences, the intent of the feeding assistance care process measures is to evaluate staff provision of optimal care for all residents in need, as defined by poor oral intake during a given mealtime period and/or an order for caloric supplementation between meals. Thus, for nutritionally at-risk residents, the defined care process measures are considered equally applicable, regardless of resident characteristics (e.g., age, gender, diagnoses, functional status).

Results revealed a trend for better mealtime care practices in the two VA study sites relative to a sample of community facilities (Schnelle et al., 2009; Simmons et al., 2002) although areas in need of improvement were still identified both during and between meals. Most notably, there was a lack of choice in the VA sites. Alternatives to the served meal were rarely offered, even for those who ate poorly, and between-meal items were preselected by staff. Given both higher staffing levels and cultural transformation initiatives in the VA (VA, 2010; Kheirbek, n.d), it is surprising that choice related to food was provided so infrequently. Other studies have shown that long term care residents value choice as it relates to food service and satisfaction with the food service is an important component of residents’ quality of life (Kane et al., 1997; West, Ouellet, Ouellette, 2003).

There are several potential explanations for the results of this study that may provide some insight into how feeding assistance care quality can be improved in the VA, as well as broader insight into the relationship between staffing levels and feeding assistance care quality. Although overall staffing was high in the two VA study sites relative to community facilities, nurse aide staffing was comparable. The higher level of staffing was due primarily to licensed nurses—not nurse aides, who are primarily responsible for mealtime feeding assistance and snacks between meals (Kayser-Jones & Schnell, 1997; Schnelle et al., 2001; Simmons & Schnelle, 2004). There may be other aspects of nutritional care more directly under the control of licensed nurses (e.g., appropriateness of prescribed diet orders, referrals for swallowing evaluations) not measured in this study that may demonstrate better care quality in the VA relative to community facilities.

The higher level of licensed nurse staffing offers an opportunity for supervision and management. However, the key to effective management is staff awareness of the areas in need of improvement and this knowledge can only be derived from accurate information about daily care processes. Similar to the results of previous studies in community facilities, the results of this study underscored, once again, that medical record documentation alone does not provide accurate information about residents’ oral intake or feeding assistance care quality (Schnelle, Osteweil, & Simmons, 2005; Simmons et al., 2002, 2003; Simmons & Reuben, 2000).

Feeding assistance care quality improved significantly in one previous study by training supervisory staff to observe mealtime care using a standardized protocol—similar to that used by research staff in this study—and provide feedback to direct care staff each week (Simmons & Schnelle, 2006a) because it increased staff awareness of missed or suboptimal care provision for individual residents. The presence of more licensed nurses should enable VA facilities to more effectively supervise and manage feeding assistance care quality using an observation-based tool (Schnelle et al., 2005; Simmons & Schnelle, 2006a). Such supervisory observations would allow staff to identify residents who are eating poorly during meals and not receiving adequate staff attention or for whom chart documentation does not accurately reflect their poor meal intake, for example. Similarly, supervisory observations also would elucidate whether or not orders for caloric supplementation between meals (via supplements or snacks) are being provided consistently in daily care practice. The results of this and previous studies underscore the need for ongoing monitoring of feeding assistance care processes to allow for continuous quality improvement and to ensure optimal care for nutritionally at-risk residents. Next steps include implementation of a staff management intervention in the VA setting utilizing a similar observational tool so that supervisory staff have accurate information about daily feeding assistance care quality. Ideally, each care process measure should have a “100% pass” rate, and higher staffing levels within the VA community living centers increases the likelihood that this is an achievable goal.

Footnotes

Acknowledgements

The authors thank the participating VA nursing homes, staff, and residents for their cooperation with this quality improvement project. The authors also thank the members of the Center for Quality Aging research team involved in the data collection.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by VA Health Services Research and Development (HSR&D) Merit Grant IRR 07-250, “Prevention of Weight Loss in Long Term Care Veterans.” The views expressed in this article are those of the authors and may not reflect those of the funding agency.

Author Biographies

Sandra F. Simmons is an Associate Professor of Medicine at the Vanderbilt Center for Quality Aging and a Research Scientist at the VA. She conducts research on quality of care and quality of life issues for older adults in the long-term care setting.

Nichole Sims is a Project Coordinator for the Vanderbilt Center for Quality Aging.

Daniel W. Durkin is a Post-Doctoral Research Fellow with the Vanderbilt Center for Quality Aging receiving training in health services research in the long-term care setting.

Matthew S. Shotwell is an Assistant Professor in the Department of Biostatistics, Vanderbilt University Medical Center. Robust nonparametric statistical methods, and statistical computing comprise Dr. Shotwell’s primary fields of research.

Scott Erwin is the Chief of Nursing Services in the VA community living center, Tennessee Valley Healthcare System.

John F. Schnelle is a Professor of Medicine, Director of the Vanderbilt Center for Quality Aging and a Research Scientist at the VA. He specializes in quality improvement and staffing issues related to care quality in the long-term care and other settings providing health care services for the elderly.

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