Evidence-based medicine: Clinical inertia: A common barrier to changing provider prescribing behavior

Vanderbilt University, USA.
Joint Commission journal on quality and patient safety / Joint Commission Resources 06/2007; 33(5):277-85.
Source: PubMed


A cross-sectional content analysis nested within a randomized, controlled trial was conducted to collect information on provider responses to computer alerts regarding guideline recommendations for patients with suboptimal hypertension care.
Participants were providers who cared for 1,017 patients with uncontrolled hypertension on a single antihypertensive agent within Veterans Affairs primary care clinics. All reasons for action or inaction were sorted into a framework to explain the variation in guideline adaptation.
The 184 negative provider responses to computer alerts contained explanations for not changing patient treatment; 76 responses to the alerts were positive, that is, the provider was going to make a change in antihypertensive regimen. The negative responses were categorized as: inertia of practice (66%), lack of agreement with specific guidelines (5%), patient-based factors (17%), environmental factors (10%), and lack of knowledge (2%). Most of the 135 providers classified as inertia of practice indicated, "Continue current medications and I will discuss at the next visit." The median number of days until the next visit was 45 days (interquartile range, 29 to 78 days).
Clinical inertia was the primary reason for failing to engage in otherwise indicated treatment change in a subgroup of patients. A framework was provided as a taxonomy for classification of provider barriers.

23 Reads
  • Source
    • "Physician, patient, and contextual factors interact to influence physician prescribing behaviors [8-11]. Physician -level barriers include: lack of knowledge and clinical skills for diabetes management [8]; time constraints [12,13]; ineffective charting systems [13-15]; clinical inertia [16,17]; and absence of organizational systems that allow adequate time and resources. In addition, physicians resist prescription of insulin due to concerns about patient weight gain, hypoglycemia, and patient expectations and fears, including injection anxiety. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Limited evidence exists on the effectiveness of external diabetes support provided by diabetes specialists and community retail pharmacists to facilitate insulin-prescribing in family practice. A stratified, parallel group, randomized control study was conducted in 15 sites across Canada. Family physicians received insulin initiation/titration education, a physician-specific 'report card' on the characteristics of their type 2 diabetes (T2DM) population, and a registry of insulin-eligible patients at a workshop. Intervention physicians in addition received: (1) diabetes specialist/educator consultation support (active diabetes specialist/educator consultation support for 2 months [the educator initiated contact every 2 weeks] and passive consultation support for 10 months [family physician initiated as needed]); and (2) community retail pharmacist support (option to refer patients to the pharmacist(s) for a 1-hour insulin-initiation session). The primary outcome was the insulin prescribing rate (IPR) per physician defined as the number of insulin starts of insulin-eligible patients during the 12-month strategy. Consenting, eligible physicians (n = 151) participated with 15 specialist sites and 107 community pharmacists providing the intervention. Most physicians were male (74%), and had an average of 81 patients with T2DM. Few (9%) routinely initiated patients on insulin. Physicians were randomly allocated to usual care (n = 78) or the intervention (n = 73). Intervention physicians had a mean (SE) IPR of 2.28 (0.27) compared to 2.29 (0.25) for control physicians, with an estimated adjusted RR (95% CI) of 0.99 (0.80 to 1.24), p = 0.96. An insulin support program utilizing diabetes experts and community retail pharmacists to enhance insulin prescribing in family practice was not successful. Too few physicians are appropriately intensifying diabetes management through insulin initiation, and aggressive therapeutic treatment is lacking. NCT00593489.
    BMC Health Services Research 02/2013; 13(1):71. DOI:10.1186/1472-6963-13-71 · 1.71 Impact Factor
  • Source
    • "GPs do not always follow guidelines in routine clinical practice [7]. They may not fully recognise the clinical importance of statin prescribing and when eligible patients consult, physicians commonly delay prescribing decisions until the next visit [8,9]. There is also confusion about which patients are eligible for treatment. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background A pilot project cardiovascular prevention was implemented in Sandwell (West Midlands, UK). This used electronic primary care records to identify untreated patients at high risk of cardiovascular disease then invited these high risk patients for assessment by a nurse in their own general practice. Those found to be eligible for treatment were offered treatment. During the pilot a higher proportion of high risk patients were started on treatment in the intervention practices than in control practices. Following the apparent success of the prevention project, it was intended to extend the service to all practices across the Sandwell area. However the pilot project was not a robust evaluation. There was a need for an efficient evaluation that would not disrupt the planned rollout of the project. Methods/design Project nurses will sequentially implement targeted cardiovascular case finding in a phased way across all general practices, with the sequence of general practices determined randomly. This is a stepped wedge randomised controlled trial design. The target population is patients aged 35 to 74, without diabetes or cardiovascular disease whose ten-year cardiovascular risk, (determined from data in their electronic records) is ≥20%. The primary outcome is the number of high risk patients started on treatment, because these data could be efficiently obtained from electronic primary care records. From this we can determine the effects of the case finding programme on the proportion of high risk patients started on treatment in practices before and after implementation of targeted case finding. Cost-effectiveness will be modelled from the predicted effects of treatments on cardiovascular events and associated health service costs. Alongside the implementation it is intended to interview clinical staff and patients who participated in the programme in order to determine acceptability to patients and clinicians. Practical considerations meant that 26 practices in Sandwell could be randomised, including about 6,250 patients at high risk of cardiovascular disease. This gives sufficient power for evaluation. Discussion It is possible to design a stepped wedge randomised controlled trial using routine data to determine the primary outcome to evaluate implementation of a cardiovascular prevention programme.
    BMC Public Health 10/2012; 12(1):908. DOI:10.1186/1471-2458-12-908 · 2.26 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This dissertation focuses on quality assessment of cardiometabolic treatment in patients with type 2 diabetes in general practice. First, methods are developed for collecting data related to diabetes care from electronic medical records. Important elements include a uniform procedure for patient selection and the extraction of relevant data from records without burdening practices with extra registration requirements. These methods were successfully implemented in the Groningen Initiative to Analyse Type 2 diabetes Treatment (GIANTT) project to build a longitudinal observational database for monitoring diabetes care. The second part concerns quality indicators for diabetes management. A comparison is made between commonly used cross-sectional indicators and newly developed “sequential” indicators which shows the value of these new indicators. A systematic review on prescribing indicators is presented, describing different types of existing indicators and their validity. Furthermore, an overview of the quality of cardiometabolic risk factor management is given, showing contrasting results for the various indicators. The third part focuses on factors mentioned as reasons not to modify cardiometabolic treatment when indicated. Some of these, e.g. using higher thresholds than recommended, waiting for the next risk factor measurement, competing demands, and medication non-adherence were found to be related to treatment decisions for hypertension and hyperglycaemia. Polypharmacy, however, was not a factor of influence. This dissertation provides new methods of obtaining information from medical records for quality assessment and scientific research. Furthermore, the usefulness of sequential indicators for quality assessment is shown. Finally, the studies on determinants of treatment modifications show targets for interventions.
Show more

Similar Publications