Objective

To assess whether a low level of decision support within a hospital computerized provider order entry system has an observable influence on the medication ordering process on ward-rounds and to assess prescribers' views of the decision support features.

Methods

14 specialty teams (46 doctors) were shadowed by the investigator while on their ward-rounds and 16 prescribers from these teams were interviewed.

Results

Senior doctors were highly influential in prescribing decisions during ward-rounds but rarely used the computerized provider order entry system. Junior doctors entered the majority of medication orders into the system, nearly always ignored computerized alerts and never raised their occurrence with other doctors on ward-rounds. Interviews with doctors revealed that some decision support features were valued but most were not perceived to be useful.

Discussion and conclusion

The computerized alerts failed to target the doctors who were making the prescribing decisions on ward-rounds. Senior doctors were the decision makers, yet the junior doctors who used the system received the alerts. As a result, the alert information was generally ignored and not incorporated into the decision-making processes on ward-rounds. The greatest value of decision support in this setting may be in non-ward-round situations where senior doctors are less influential. Identifying how prescribing systems are used during different clinical activities can guide the design of decision support that effectively supports users in different situations. If confirmed, the findings reported here present a specific focus and user group for designers of medication decision support.

Background

The adoption of new medicines is influenced by a complex set of social processes that have been widely examined in terms of individual prescribers’ information-seeking and decision-making behaviour. However, quantitative, population-wide analyses of how long it takes for new healthcare practices to become part of mainstream practice are rare.

Methods

We applied a Bass diffusion model to monthly prescription volumes of 103 often-prescribed drugs in Australia (monthly time series data totalling 803 million prescriptions between 1992 and 2010), to determine the distribution of adoption rates. Our aim was to test the utility of applying the Bass diffusion model to national-scale prescribing volumes.

Results

The Bass diffusion model was fitted to the adoption of a broad cross-section of drugs using national monthly prescription volumes from Australia (median R2 = 0.97, interquartile range 0.95 to 0.99). The median time to adoption was 8.2 years (IQR 4.9 to 12.1). The model distinguished two classes of prescribing patterns – those where adoption appeared to be driven mostly by external forces (19 drugs) and those driven mostly by social contagion (84 drugs). Those driven more prominently by internal forces were found to have shorter adoption times (p = 0.02 in a non-parametric analysis of variance by ranks).

Conclusion

The Bass diffusion model may be used to retrospectively represent the patterns of adoption exhibited in prescription volumes in Australia, and distinguishes between adoption driven primarily by external forces such as regulation, or internal forces such as social contagion. The eight-year delay between the introduction of a new medicine and the adoption of the prescribing practice suggests the presence of system inertia in Australian prescribing practices.

In a before-and-after study, Johanna Westbrook and colleagues evaluate the change in prescribing error rates after the introduction of two commercial electronic prescribing systems in two Australian hospitals.

Background

Considerable investments are being made in commercial electronic prescribing systems (e-prescribing) in many countries. Few studies have measured or evaluated their effectiveness at reducing prescribing error rates, and interactions between system design and errors are not well understood, despite increasing concerns regarding new errors associated with system use. This study evaluated the effectiveness of two commercial e-prescribing systems in reducing prescribing error rates and their propensities for introducing new types of error.

Methods and Results

We conducted a before and after study involving medication chart audit of 3,291 admissions (1,923 at baseline and 1,368 post e-prescribing system) at two Australian teaching hospitals. In Hospital A, the Cerner Millennium e-prescribing system was implemented on one ward, and three wards, which did not receive the e-prescribing system, acted as controls. In Hospital B, the iSoft MedChart system was implemented on two wards and we compared before and after error rates. Procedural (e.g., unclear and incomplete prescribing orders) and clinical (e.g., wrong dose, wrong drug) errors were identified. Prescribing error rates per admission and per 100 patient days; rates of serious errors (5-point severity scale, those ≥3 were categorised as serious) by hospital and study period; and rates and categories of postintervention “system-related” errors (where system functionality or design contributed to the error) were calculated. Use of an e-prescribing system was associated with a statistically significant reduction in error rates in all three intervention wards (respectively reductions of 66.1% [95% CI 53.9%–78.3%]; 57.5% [33.8%–81.2%]; and 60.5% [48.5%–72.4%]). The use of the system resulted in a decline in errors at Hospital A from 6.25 per admission (95% CI 5.23–7.28) to 2.12 (95% CI 1.71–2.54; p<0.0001) and at Hospital B from 3.62 (95% CI 3.30–3.93) to 1.46 (95% CI 1.20–1.73; p<0.0001). This decrease was driven by a large reduction in unclear, illegal, and incomplete orders. The Hospital A control wards experienced no significant change (respectively −12.8% [95% CI −41.1% to 15.5%]; −11.3% [−40.1% to 17.5%]; −20.1% [−52.2% to 12.4%]). There was limited change in clinical error rates, but serious errors decreased by 44% (0.25 per admission to 0.14; p = 0.0002) across the intervention wards compared to the control wards (17% reduction; 0.30–0.25; p = 0.40). Both hospitals experienced system-related errors (0.73 and 0.51 per admission), which accounted for 35% of postsystem errors in the intervention wards; each system was associated with different types of system-related errors.

Conclusions

Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates. Reductions in clinical errors were limited in the absence of substantial decision support, but a statistically significant decline in serious errors was observed. System-related errors require close attention as they are frequent, but are potentially remediable by system redesign and user training. Limitations included a lack of control wards at Hospital B and an inability to randomize wards to the intervention.

Please see later in the article for the Editors' Summary

Editors' Summary

Background

Medication errors—for example, prescribing the wrong drug or giving a drug by the wrong route—frequently occur in health care settings and are responsible for thousands of deaths every year. Until recently, medicines were prescribed and dispensed using systems based on hand-written scripts. In hospitals, for example, physicians wrote orders for medications directly onto a medication chart, which was then used by the nursing staff to give drugs to their patients. However, drugs are now increasingly being prescribed using electronic prescribing (e-prescribing) systems. With these systems, prescribers use a computer and order medications for their patients with the help of a drug information database and menu items, free text boxes, and prewritten orders for specific conditions (so-called passive decision support). The system reviews the patient's medication and known allergy list and alerts the physician to any potential problems, including drug interactions (active decision support). Then after the physician has responded to these alerts, the order is transmitted electronically to the pharmacy and/or the nursing staff who administer the prescription.

Why Was This Study Done?

By avoiding the need for physicians to write out prescriptions and by providing active and passive decision support, e-prescribing has the potential to reduce medication errors. But, even though many countries are investing in expensive commercial e-prescribing systems, few studies have evaluated the effects of these systems on prescribing error rates. Moreover, little is known about the interactions between system design and errors despite fears that e-prescribing might introduce new errors. In this study, the researchers analyze prescribing error rates in hospital in-patients before and after the implementation of two commercial e-prescribing systems.

What Did the Researchers Do and Find?

The researchers examined medication charts for procedural errors (unclear, incomplete, or illegal orders) and for clinical errors (for example, wrong drug or dose) at two Australian hospitals before and after the introduction of commercial e-prescribing systems. At Hospital A, the Cerner Millennium e-prescribing system was introduced on one ward; three other wards acted as controls. At Hospital B, the researchers compared the error rates on two wards before and after the introduction of the iSoft MedChart e-prescribing system. The introduction of an e-prescribing system was associated with a substantial reduction in error rates in the three intervention wards; error rates on the control wards did not change significantly during the study. At Hospital A, medication errors declined from 6.25 to 2.12 per admission after the introduction of e-prescribing whereas at Hospital B, they declined from 3.62 to 1.46 per admission. This reduction in error rates was mainly driven by a reduction in procedural error rates and there was only a limited change in overall clinical error rates. Notably, however, the rate of serious errors decreased across the intervention wards from 0.25 to 0.14 per admission (a 44% reduction), whereas the serious error rate only decreased by 17% in the control wards during the study. Finally, system-related errors (for example, selection of an inappropriate drug located on a drop-down menu next to a likely drug selection) accounted for 35% of errors in the intervention wards after the implementation of e-prescribing.

What Do These Findings Mean?

These findings show that the implementation of these two e-prescribing systems markedly reduced hospital in-patient prescribing error rates, mainly by reducing the number of incomplete, illegal, or unclear medication orders. The limited decision support built into both the e-prescribing systems used here may explain the limited reduction in clinical error rates but, importantly, both e-prescribing systems reduced serious medication errors. Finally, the high rate of system-related errors recorded in this study is worrying but is potentially remediable by system redesign and user training. Because this was a “real-world” study, it was not possible to choose the intervention wards randomly. Moreover, there was no control ward at Hospital B, and the wards included in the study had very different specialties. These and other aspects of the study design may limit the generalizability of these findings, which need to be confirmed and extended in additional studies. Even so, these findings provide persuasive evidence of the current and potential ability of commercial e-prescribing systems to reduce prescribing errors in hospital in-patients provided these systems are continually monitored and refined to improve their performance.

Additional Information

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001164.

ClinfoWiki has pages on medication errors and on electronic prescribing (note: the Clinical Informatics Wiki is a free online resource that anyone can add to or edit)

Electronic prescribing in hospitals challenges and lessons learned describes the implementation of e-prescribing in UK hospitals; more information about e-prescribing in the UK is available on the NHS Connecting for Health Website

The Clinicians Guide to e-Prescribing provides up-to-date information about e-prescribing in the USA

Information about e-prescribing in Australia is also available

Information about electronic health records in Australia

Introduction

In recent years in keeping with international best practice, clinical guidelines for common conditions have been developed, endorsed and disseminated by peak national and professional bodies. Yet evidence suggests that there remain considerable gaps between the care that is regarded as appropriate by such guidelines and the care received by patients. With an ageing population and increasing treatment options and expectations, healthcare is likely to become unaffordable unless more appropriate care is provided. This paper describes a study protocol that seeks to determine the percentage of healthcare encounters in which patients receive appropriate care for 22 common clinical conditions and the reasons why variations exist from the perspectives of both patients and providers.

Methods/design

A random stratified sample of at least 1000 eligible participants will be recruited from a representative cross section of the adult Australian population. Participants' medical records from the years 2009 and 2010 will be audited to assess the appropriateness of the care received for 22 common clinical conditions by determining the percentage of healthcare encounters at which the care provided was concordant with a set of 522 indicators of care, developed for these conditions by a panel of 43 disease experts. The knowledge, attitudes and beliefs of participants and healthcare providers will be examined through interviews and questionnaires to understand the factors influencing variations in care.

Ethics and dissemination

Primary ethics approvals were sought and obtained from the Hunter New England Local Health Network. The authors will submit the results of the study to a relevant journal as well as undertaking oral presentations to researchers, clinicians and policymakers.

Article summary

Article focus

What is the percentage of healthcare encounters at which Australians receive appropriate care?

What influences variations in care from the perspectives of patients and healthcare providers?

Key messages

A protocol for a population-based study of appropriate care of 1000 patients using medical record review.

Strengths and limitations of this study

Obtaining a snapshot and using a consistent method for 522 indicators across 22 common conditions power diagnostic indicators because they only present once for each patient.

The potential attrition rate of healthcare providers and telephone recruitment of participants may introduce selection biases.

Objective

To examine the effect of interruptions and task complexity on error rates when prescribing with computerized provider order entry (CPOE) systems, and to categorize the types of prescribing errors.

Design

Two within-subject factors: task complexity (complex vs simple) and interruption (interruption vs no interruption). Thirty-two hospital doctors used a CPOE system in a computer laboratory to complete four prescribing tasks, half of which were interrupted using a counterbalanced design.

Measurements

Types of prescribing errors, error rate, resumption lag, and task completion time.

Results

Errors in creating and updating electronic medication charts that were measured included failure to enter allergy information; selection of incorrect medication, dose, route, formulation, or frequency of administration from lists and drop-down menus presented by the CPOE system; incorrect entry or omission in entering administration times, start date, and free-text qualifiers; and omissions in prescribing and ceasing medications. When errors occurred, the error rates across the four prescribing tasks ranged from 0.5% (1 incorrect medication selected out of 192 chances for selecting a medication or error opportunities) to 16% (5 failures to enter allergy information out of 32 error opportunities). Any impact of interruptions on prescribing error rates and task completion times was not detected in our experiment. However, complex tasks took significantly longer to complete (F(1, 27)=137.9; p<0.001) and when execution was interrupted they required almost three times longer to resume compared to simple tasks (resumption lag complex=9.6 seconds, SD=5.6; resumption lag simple=3.4 seconds, SD=1.7; t(28)=6.186; p<0.001).

Conclusion

Most electronic prescribing errors found in this study could be described as slips in using the CPOE system to create and update electronic medication charts. Cues available within the user interface may have aided resumption of interrupted tasks making CPOE systems robust to some interruption effects. Further experiments are required to rule out any effect interruption might have on CPOE error rates.

Investigation of the genetic basis of hyperuricaemia is a subject of intense interest. However, clinical studies commonly include hyperuricaemic patients without distinguishing between 'over-producers' or 'under-excretors' of urate. The statistical power of studies of genetic polymorphisms of genes encoding renal urate transporters is diluted if 'over-producers' of uric acid are included. We propose that lower than normal fractional renal clearance of urate is a better inclusion criterion for these studies. We also propose that a single daytime spot urine sample for calculation of fractional renal clearance of urate should be preferred to calculation from 24-hour urine collections.

Background

A number of health benefits including improvements in acid/base balance, bone metabolism, and cardiovascular risk factors have been attributed to the intake of magnesium rich alkaline mineral water. This study was designed to investigate the effects of the regular consumption of magnesium bicarbonate supplemented spring water on pH, biochemical parameters of bone metabolism, lipid profile and blood pressure in postmenopausal women.

Findings

In this double-blind, placebo-controlled, parallel-group, study, 67 postmenopausal women were randomised to receive between 1500 mL and 1800 mL daily of magnesium bicarbonate supplemented spring water (650 mg/L bicarbonate, 120 mg/L magnesium, pH 8.3-8.5) (supplemented water group) or spring water without supplements (control water group) over 84 days. Over this period biomarkers of bone turnover (serum parathyroid hormone (PTH), 1,25-dihydroxyvitamin D, osteocalcin, urinary telopeptides and hydroxyproline), serum lipids (total cholesterol, HDL-cholesterol, LDL-cholesterol and triglycerides), venous and urinary pH were measured together with measurements of standard biochemistry, haematology and urine examinations.

Serum magnesium concentrations and urinary pH in subjects consuming the magnesium bicarbonate supplemented water increased significantly at Day 84 compared to subjects consuming the spring water control (magnesium - p = 0.03; pH - p = 0.018). The consumption of spring water led to a trend for an increase in parathyroid hormone (PTH) concentrations while the PTH concentrations remained stable with the intake of the supplemented spring water. However there were no significant effects of magnesium bicarbonate supplementation in changes to biomarkers of bone mineral metabolism (n-telopeptides, hydroxyproline, osteocalcin and 1,25-dihydroxyvitamin D) or serum lipids or blood pressure in postmenopausal women from Day 0 to Day 84.

Conclusions

Short term regular ingestion of magnesium bicarbonate supplemented water provides a source of orally available magnesium. Long term clinical studies are required to investigate any health benefits.

Trial registration

ACTRN12609000863235

Previous reviews have examined evidence of the impact of CPOE on medication errors, but have used highly variable definitions of “error”. We attempted to answer a very focused question, namely, what evidence exists that CPOE systems reduce prescribing errors among hospital inpatients? We identified 13 papers (reporting 12 studies) published between 1998 and 2007. Nine demonstrated a significant reduction in prescribing error rates for all or some drug types. Few studies examined changes in error severity, but minor errors were most often reported as decreasing. Several studies reported increases in the rate of duplicate orders and failures to discontinue drugs, often attributed to inappropriate selection from a dropdown menu or to an inability to view all active medication orders concurrently. The evidence-base reporting the effectiveness of CPOE to reduce prescribing errors is not compelling and is limited by modest study sample sizes and designs. Future studies should include larger samples including multiple sites, controlled study designs, and standardized error and severity reporting. The role of decision support in minimizing severe prescribing error rates also requires investigation.

Background

Provision of online evidence at the point of care is one strategy that could provide clinicians with easy access to up-to-date evidence in clinical settings in order to support evidence-based decision making.

Objective

The aim was to determine long-term use of an online evidence system in routine clinical practice.

Methods

This was a prospective cohort study. 59 clinicians who had a computer with Internet access in their consulting room participated in a 12-month trial of Quick Clinical, an online evidence system specifically designed around the needs of general practitioners (GPs). Patterns of use were determined by examination of computer logs and survey analysis.

Results

On average, 9.9 searches were conducted by each GP in the first 2 months of the study. After this, usage dropped to 4.4 searches per GP in the third month and then levelled off to between 0.4 and 2.6 searches per GP per month. The majority of searches (79.2%, 2013/2543) were conducted during practice hours (between 9 am and 5 pm) and on weekdays (90.7%, 2315/2543). The most frequent searches related to diagnosis (33.6%, 821/2291) and treatment (34.5%, 844/2291).

Conclusion

GPs will use an online evidence retrieval system in routine practice; however, usage rates drop significantly after initial introduction of the system. Long-term studies are required to determine the extent to which GPs will integrate the use of such technologies into their everyday clinical practice and how this will affect the satisfaction and health outcomes of their patients.

Background

Subsidised access to high-cost medicines in Australia is restricted under national programs (the Pharmaceutical Benefits Scheme, PBS, and the Repatriation Pharmaceutical Benefits Scheme, RPBS) with a view to achieving cost-effective use. The aim of this study was to examine the use and associated government cost of biological agents for treating rheumatoid arthritis over the first two years of subsidy, and to compare these data to the predicted outcomes.

Methods

National prescription and expenditure data for the biologicals, etanercept, infliximab, adalimumab, and anakinra were collected and analysed for the period August 2003 to July 2005. Dispensing data on biologicals sorted by the metropolitan, rural and remote zones and by prescriber major specialty were also examined.

Results

A total of 27,970 prescriptions for biologicals was reimbursed. The government expenditure was A$53.1 million, representing only 19% of that expected. Almost all prescriptions were reimbursed by the PBS (98%, A$52 million) and the remainder by the RPBS. Approximately 62% of the prescriptions were for concessional patients (A$32.9 million). There was considerable variability in the use of biologicals across Australian states and territories, usage roughly correlating with the per capita adjusted number of rheumatologists. The total number of prescriptions continued to increase over the study period. Etanercept was the most highly prescribed agent (74% by number of prescriptions), although its use was beginning to plateau. Use of adalimumab increased steadily. Use of infliximab and anakinra was considerably lower. The resultant health outcomes for individual patients are unknown. Prescribers from capital cities and other metropolitan centres provided a majority of prescriptions of biologicals (89%).

Conclusion

The overall uptake of biologicals for treating rheumatoid arthritis over the first two years of PBS subsidy was considerably lower than expected. Long-term safety concerns and the expanded clinical uses of these drugs emphasise the need for evaluation. It is essential that there is comprehensive, ongoing analysis of utilisation data, associated expenditure and, importantly, patient outcomes in order to enhance accountability, efficiency and equity of policies that allocate substantial resources to subsidising national access to high-cost medicines.

Background

Online information retrieval systems have the potential to improve patient care but there are few comparative studies of the impact of online evidence on clinicians' decision-making behaviour in routine clinical work.

Methods/design

A randomized controlled parallel design is employed to assess the effectiveness of an online evidence retrieval system, Quick Clinical (QC) in improving clinical decision-making processes in general practice. Eligible clinicians are randomised either to receive access or not to receive access to QC in their consulting rooms for 12 months. Participants complete pre- and post trial surveys.

Two-hundred general practitioners are recruited. Participants must be registered to practice in Australia, have a computer with Internet access in their consulting room and use electronic prescribing. Clinicians planning to retire or move to another practice within 12 months or participating in any other clinical trial involving electronic extraction of prescriptions data are excluded from the study.

The primary end-points for the study is clinician acceptance and use of QC and the resulting change in decision-making behaviour. The study will examine prescribing patterns related to frequently prescribed medications where there has been a recent significant shift in recommendations regarding their use based upon new evidence. Secondary outcome measures include self-reported changes in diagnosis, patient education, prescriptions written, investigations and referrals.

Discussion

A trial under experimental conditions is an effective way of examining the impact of using QC in routine general practice consultations.

Background

In Australia, the Pharmaceutical Benefits Scheme (PBS) has developed a set of arrangements to control access to high-cost medicines to ensure their use is cost-effective. These medicines include the tumour necrosis factor-alpha inhibitors (TNFIs) for the treatment of rheumatoid arthritis. The aim of this first phase of a qualitative study was to explore basic views on the restricted access to TNFIs in order to confirm where further investigation should take place in the next phase.

Methods

Semi-structured interviews were conducted in 2004 with a member of the four relevant stakeholder groups. Participants were asked their opinions about features of the establishment, process and effects of the system of restricted access to TNFIs. Views on the collaboration between stakeholder groups in the decision-making process were also collected.

Results

The principle of 'controlled access' to TNFIs was supported in general. There were concerns regarding some of the specific eligibility criteria. Wider and more transparent stakeholder consultation was judged desirable. Some flexibility around prescribing of TNFIs by physicians, and regular review of the arrangements were proposed. These themes will inform the next phase of the study.

Conclusion

This first phase highlighted a range of issues associated with the PBS arrangements restricting access to TNFIs. Timely review and report of issues and concerns associated with such policy developments that arose in practice are essential. There is a need for a more comprehensive exploration across a wide range of stakeholders with different perspectives that will in turn be helpful in guiding policy and practice around national arrangements to manage access to high-cost medicines.

Introduction

Hyperuricemia is the greatest risk factor for gout and is caused by an overproduction and/or inefficient renal clearance of urate. The fractional renal clearance of urate (FCU, renal clearance of urate/renal clearance of creatinine) has been proposed as a tool to identify subjects who manifest inefficient clearance of urate. The aim of the present studies was to validate the measurement of FCU by using spot-urine samples as a reliable indicator of the efficiency of the kidney to remove urate and to explore its distribution in healthy subjects and gouty patients.

Methods

Timed (spot, 2-hour, 4-hour, 6-hour, 12-hour, and 24-hour) urine collections were used to derive FCU in 12 healthy subjects. FCUs from spot-urine samples were then determined in 13 healthy subjects twice a day, repeated on 3 nonconsecutive days. The effect of allopurinol, probenecid, and the combination on FCU was explored in 11 healthy subjects. FCU was determined in 36 patients with gout being treated with allopurinol. The distribution of FCU was examined in 118 healthy subjects and compared with that from the 36 patients with gout.

Results

No substantive or statistically significant differences were observed between the FCUs derived from spot and 24-hour urine collections. Coefficients of variation (CVs) were both 28%. No significant variation in the spot FCU was obtained either within or between days, with mean intrasubject CV of 16.4%. FCU increased with probenecid (P < 0.05), whereas allopurinol did not change the FCU in healthy or gouty subjects. FCUs of patients with gout were lower than the FCUs of healthy subjects (4.8% versus 6.9%; P < 0.0001).

Conclusions

The present studies indicate that the spot-FCU is a convenient, valid, and reliable indicator of the efficiency of the kidney in removing urate from the blood and thus from tissues. Spot-FCU determinations may provide useful correlates in studies investigating molecular mechanisms underpinning the observed range of efficiencies of the kidneys in clearing urate from the blood.

Trial Registration

ACTRN12611000743965

Background

Clinical practice guidelines recommend that the initial treatment of acute low back pain (LBP) should consist of advice to stay active and regular simple analgesics such as paracetamol 4 g daily. Despite this recommendation in all international LBP guidelines there are no placebo controlled trials assessing the efficacy of paracetamol for LBP at any dose or dose regimen. This study aims to determine whether 4 g of paracetamol daily (in divided doses) results in a more rapid recovery from acute LBP than placebo. A secondary aim is to determine if ingesting paracetamol in a time-contingent manner is more effective than paracetamol taken when required (PRN) for recovery from acute LBP.

Methods/Design

The study is a randomised double dummy placebo controlled trial. 1650 care seeking people with significant acute LBP will be recruited. All participants will receive advice to stay active and will be randomised to 1 of 3 treatment groups: time-contingent paracetamol dose regimen (plus placebo PRN paracetamol), PRN paracetamol (plus placebo time-contingent paracetamol) or a double placebo study arm. The primary outcome will be time (days) to recovery from pain recorded in a daily pain diary. Other outcomes will be pain intensity, disability, function, global perceived effect and sleep quality, captured at baseline and at weeks 1, 2, 4 and 12 by an assessor blind to treatment allocation. An economic analysis will be conducted to determine the cost-effectiveness of treatment from the health sector and societal perspectives.

Discussion

The successful completion of the trial will provide the first high quality evidence on the effectiveness of the use of paracetamol, a guideline endorsed treatment for acute LBP.

Trail registration

ACTRN12609000966291.

Background

Acute low back pain is a common condition resulting in pain and disability. Current national and international guidelines advocate general practitioner care including advice and paracetamol (4 g daily in otherwise well adults) as the first line of care for people with acute low back pain. Non-steroidal anti-inflammatory drugs (NSAIDs) and spinal manipulative therapy (SMT) are advocated in many guidelines as second line management options for patients with acute low back pain who are not recovering. No studies have explored the role of NSAIDs and/or SMT in addition to first line management for acute low back pain. The primary aim of this study is to investigate if NSAIDs and/or SMT in addition to general practitioner advice and paracetamol results in shorter recovery times for patients with acute low back pain. The secondary aims of the study are to evaluate whether the addition of SMT and/or NSAIDs influences pain, disability and global perceived effect at 1, 2, 4 and 12 weeks after onset of therapy for patients with significant acute low back pain.

Methods/design

This paper presents the rationale and design of a randomised controlled trial examining the addition of NSAIDs and/or SMT in 240 people who present to their general practitioner with significant acute low back pain.