SUPPORT Summaries
Evidence of the effects of health system interventions
for low- and middle-income countries
Evidence of the effects of health system interventions
for low- and middle-income countries
March, 2017 - SUPPORT Summary of a systematic review | print this article | download PDF
Many countries have introduced new nurse staffing models in hospitals to respond to changing patient care needs and shortages of qualified nursing staff. These new models include changes in the mix of skills, qualifications or staffing levels within the hospital workforce, and changes in nursing shifts or work patterns. Nurse staffing might be associated with the quality of care that patients receive and with patient outcomes.
A summary of studies addressing a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise the relevant research, and to collect and analyse data from the included studies.
SUPPORT – was an international project to support the use of policy relevant reviews and trials to inform decisions about maternal and child health in low- and middle-income countries, funded by the European Commission (FP6) and the Canadian Institutes of Health Research.
Hospitalised patients have become more seriously ill, requiring more intensive nursing care and ageing populations are further stretching nursing resources. A range of nurse staffing model interventions has been introduced across countries to address nursing shortages. These models include changes to nurse staffing levels and skill mix, changes in nurse education, changes to staff allocation models and shift patterns, and greater use of overtime and agency staff. The numbers of nurses available in a hospital or hospital unit (staffing levels) can be quantified in relation to the nurse per patient ratio or in terms of hours of nursing care. Skill mix may refer to the mix of “licensed/registered” and “unlicensed/unregistered” staff or the proportion of different nursing levels of qualification, expertise, or experience.
| Review objectives: To determine the effect of hospital nurse staffing models on patient and staff-related outcomes | ||
| Type of | What the review authors searched for | What the review authors found |
|---|---|---|
| Study designs & interventions | Randomised trials, non-randomised trials, controlled before- after studies, and interrupted time series studies of interventions relating to hospital nurse staffing models |
15 studies (8 randomised trials, 2 non-randomised trials, and 5 controlled before- after studies). 4 studies assessed primary nursing, self-scheduling, and team midwifery; and 11 studies related to nursing skill-mix (9 examining the addition of specialist nurses to usual staffing; 2 examining increases in the proportion of support staff versus usual nursing staff). |
| Participants | Patients and nursing staff |
Nursing staff: midwives; surgical, medical and gynaecological ward nurses; nurse case managers; clinical nurse specialists; nursing assistants; advance practice nurses Patients: pregnant women; women scheduled for surgery; women admitted with hip fractures; people with breast cancer, diabetes, mental health problems, multiple sclerosis, myocardial infarctions |
| Settings | Hospital settings worldwide |
Unites States (7), United Kingdom (4), Australia (1), The Netherlands (2), and Canada (1) |
| Outcomes | Any objective measure of patient or staff-related outcome |
Staff-related outcomes: absenteeism, staff retention and staff turnover; Patient outcomes: patient falls, medication errors and adverse incidents, length of stay, patient mortality, re-admission and attendance at the emergency department post-discharge; and Costs |
| Date of most recent search: May 2009 | ||
| Limitations:This is well-conducted systematic review with only minor limitations. | ||
Butler M, Collins R, Drennan J, et al. Hospital nurse staffing models and patient and staff-related outcomes. Cochrane Database Syst Rev 2011; (7):CD007019.
High: This research provides a very good indication of the likely effect. The likelihood that the effect will be substantially different† is low.
Moderate: This research provides a good indication of the likely effect. The likelihood that effect will be substantially different† is moderate.
Low: This research provides some indication of the likely effect. Howevver, the likelihood that it will be substantially different† is high.
Very low: This research does not provide a reliable indication of the likely effect. The likelihood that the effect will be substantially different† is very high.
* This is sometimes referred to as 'quality of evidence' or 'confidence in the estimate'.
† Substantially different = a large enough difference that it might affect a decision.
See last page for more information.
15 studies were included on the impacts of nurse staffing models.
The impact of specialist nursing roles on patient outcomes was assessed in eight studies. Specialist nurse roles varied from study to study, but all were focused around the needs of specific groups of patients, such as patients with diabetes, multiple sclerosis, myocardial infarction, mental health problems, or gynaecological problems. The role of the specialist nurse usually involved co-ordinating care, including arranging tests and procedures, assessing patients, planning their care and reviewing their progress, undertaking or prescribing specific interventions based on assessed needs, and educating patients, nurses, and other staff.
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Adding a specialist nursing post to nurse staffing compared to usual nurse staffing |
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People Patients with a range of health issues Settings Hospital Intervention The addition of a specialist nursing post(s) to staffing Comparison Usual nurse staffing |
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| Outcomes | Usual nurse staffing | The addition of a specialist nursing post(s) to staffing | Relative effect (95% CI) |
Certainty of the evidence (GRADE) |
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| Absolute effect (95% CI) | ||||||
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In-hospital mortality |
97 per 1000 |
93 per 1000 (57 to 151) |
RR 0.96 (0.59 to 1.56) |
Low |
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Re-admission Study population |
174 per 1000 |
200 per 1000 (153 to 264) |
RR 1.15 |
Low |
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Medium risk* population |
144 per 1000 |
166 per 1000 (127 to 219) |
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Attendance at ED within 30 days |
192 per 1000 |
219 per 1000 (152 to 311) |
RR 1.14 (0.79 to 1.62) |
Low |
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Post-discharge adverse events# |
228 per 1000 |
235 per 1000 (160 to 349) |
RR 1.03 (0.7 to 1.53) |
Low |
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Patient length of stay |
1.35 fewer days (1.92 to 0.78 fewer days) |
Low |
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Margin of error = Confidence interval (95% CI) RR: Risk ratio GRADE: GRADE Working Group grades of evidence (see above and last page) *The assumed risks are drawn from the control group risk across the studies and in part imply patients with less serious health problems. # One study found that the use of specialist nurses may reduce the incidence of pressure ulcers. |
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The review identified two studies that assessed the addition of dietetic technicians to nurse staffing. This staff, trained (during one or two years) in dietetics and nutrition care, is involved in planning, implementing and monitoring nutritional programs and services in facilities.
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Adding dietary assistants to nurse staffing compared to usual nurse staffing |
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People Women aged over 65 admitted to a single trauma ward with hip fracture Settings Hospital Intervention The addition of dietary assistants (with 14 days of orientation and training) to nurse staffing Comparison Usual nurse staffing |
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| Outcomes | Usual nurse staffing | Adding dietary assistants to nurse staffing | Relative effect (95% CI) | Certainty of the evidence (GRADE) | ||
| Absolute effect (95% CI) | ||||||
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Mortality - Deaths in trauma unit |
102 per 1000 |
42 per 1000 (16 to 103) |
RR 0.41 (0.16 to 1.01) |
Low |
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Mortality - Deaths in hospital |
146 per 1000 |
82 per 1000 (43 to 160) |
RR 0.56 (0.29 to 1.09) |
Low |
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Mortality - Deaths at 4 months after discharge |
229 per 1000 |
131 per 1000 (78 to 218) |
RR 0.57 (0.34 to 0.95) |
Low |
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Margin of error = Confidence interval (95% CI) RR: Risk ratio GRADE: GRADE Working Group grades of evidence (see above and last page) |
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One study that examined the effect of introducing a self-scheduling system on staff-related outcomes found that this may lead to a reduction in staff turnover. The certainty of this evidence is low.
Primary nursing is a system for the distribution of nursing care in which care of one patient is managed for the entire 24-hour day by one nurse who directs and coordinates nurses and other personnel. Two studies examined the effect of introducing primary nursing on staff-related outcomes. The effect of these interventions on absenteeism and turnover rates is uncertain because the evidence is of very low certainty.
The introduction of team midwifery (defined as a group of midwives providing care and taking shared responsibility for a group of women from the antenatal period through the intrapartum and postnatal periods) versus standard care, was evaluated in one study.
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Team midwifery compared to standard maternity care |
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People Patients with maternity care outcomes Settings Hospital Intervention Team midwifery Comparison Standard care |
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| Outcomes | Standard maternity care | Use of team midwifery | Relative effect (95% CI) |
Certainty of the evidence (GRADE) |
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| Absolute effect (95% CI) | ||||||
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Perinatal deaths |
9 per 1000 |
11 per 1000 (3 to 40) |
RR 1.22 (0.33 to 4.5) |
Moderate |
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Length of stay in special care nursery for infants |
2 fewer days (2.07 to 1.93 lower) |
High |
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Length of stay in hospital for women giving birth |
0.3 fewer days (0.54 to 0.06 fewer days) |
High |
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Margin of error = Confidence interval (95% CI) RR: Risk ratio GRADE: GRADE Working Group grades of evidence (see above and last page) |
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| Findings | Interpretation* |
|---|---|
| APPLICABILITY | |
| The trials included in the review were conducted in high-income countries. |
When assessing the transferability of these findings to low-income countries the following factors should be considered: − The availability and training of nurses − The acceptability, feasibility and costs of different nurse staffing models. In particular, nurse and other health professional associations may need to be consulted The ability of the health system and hospitals to support the implementation of new nurse staffing models |
| EQUITY | |
| There was no information in the included studies regarding the differential effects of the interventions on resource-disadvantaged populations. |
The resources needed for training may be less available in disadvantaged settings. These interventions may increase inequities if they are not applied or adapted to populations in rural or remote areas. |
| ECONOMIC CONSIDERATIONS | |
| The systematic review did not address economic considerations. |
Scaling up nurse staffing will require resources, and a well functioning and coordinated health system. Local cost studies should be considered prior to scaling up nurse staffing. |
| MONITORING & EVALUATION | |
| There is little evidence from rigorous studies for several of the comparisons considered in this review. |
Larger and more rigorous studies to determine the effects and the cost-effectiveness of alternative nurse staffing models and educational interventions are needed, particualarly in low-income countries. |
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*Judgements made by the authors of this summary, not necessarily those of the review authors, based on the findings of the review and consultation with researchers and policymakers in low-income countries. For additional details about how these judgements were made see: www.supportsummaries.org/methods |
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This systematic review provides information about team midwifery:
Sandall J, Soltani H, Gates S, et al. Midwife-led continuity models versus other models of care for childbearing women. Cochrane Database Syst Rev 2013; (8):CD004667.
Agustín Ciapponi, Instituto de Efectividad Clínica y Sanitaria, Buenos Aires, Argentina
None declared. For details, see: www.supportsummaries.org/coi
This summary has been peer reviewed by: Michelle Butler and Laetitia Rispel.
Butler M, Collins R, Drennan J, et al. Hospital nurse staffing models and patient and staff-related outcomes. Cochrane Database Syst Rev 2011; (7):CD007019.
Keywords
evidence-informed health policy, evidence-based, systematic review, health systems research, health care, low and middle-income countries, developing countries, primary health care, models, nursing, nursing staff, hospital, outcome assessment (health care); personnel staffing and scheduling
