The effect of feedback to general practitioners on quality of care for people with type 2 diabetes. A systematic review of the literature

Background There have been numerous efforts to improve and assure the quality of treatment and follow-up of people with Type 2 diabetes (PT2D) in general practice. Facilitated by the increasing usability and validity of guidelines, indicators and databases, feedback on diabetes care is a promising tool in this aspect. Our goal was to assess the effect of feedback to general practitioners (GPs) on the quality of care for PT2D based on the available literature. Methods Systematic review searches were conducted using October 2008 updates of Medline (Pubmed), Cochrane library and Embase databases. Additional searches in reference lists and related articles were conducted. Papers were included if published in English, performed as randomized controlled trials, studying diabetes, having general practice as setting and using feedback to GPs on diabetes care. The papers were assessed according to predefined criteria. Results Ten studies complied with the inclusion criteria. Feedback improved the care for PT2D, particularly process outcomes such as foot exams, eye exams and Hba1c measurements. Clinical outcomes like lowering of blood pressure, Hba1c and cholesterol levels were seen in few studies. Many process and outcome measures did not improve, while none deteriorated. Meta analysis was unfeasible due to heterogeneity of the studies included. Two studies used electronic feedback. Conclusion Based on this review, feedback seems a promising tool for quality improvement in diabetes care, but more research is needed, especially of electronic feedback.


Background
In our efforts to improve and assure the quality of care in general practice, information technology is becoming increasingly used [1]. Quality improvement tools for diabetes, often delivered electronically, include general information and clinical guidelines, feedback on the quality of care as well as patient information letters. Furthermore, many general practitioners (GPs) use electronic patient's records. The use of information technology in general practice is facilitated by the increasing numbers and validity of clinical databases [2]. These databases make it possible to extract accurate information in an easy and low cost way.
In 2006, a Cochrane review concluded that "Audit and feedback can be effective in improving professional practice (...) the relative effectiveness of audit and feedback is likely to be greater when baseline adherence to recommended practice is low (...) [3].
Recent published figures [4] show that 88% of native Danish PT2D had their Hba1c measured at least once during year 2003; for eye examinations the figure was 33% increasing to only 61% over a four year period. 70% of the native Danish PT2Ds had an annual serum cholesterol measurement. These figures show that there is room for improvement when it comes to caring for PT2Ds.
Recent reviewing of prompting clinicians about preventive care measures have revealed a modest consequence, with cardiac care and smoking cessation reminders being most effective [5]. The aim of this paper was to review the available literature on the effect of feedback on diabetes care in general practice, and more specifically whether there was an effect of feedback to GPs on process and outcome measures for the quality of care for PT2D and to what extent electronic feedback had been investigated. We define feedback as "any summary of clinical performance of health care over a specified period of time". Electronic feedback is defined in the same way but delivered to the end user via computer [3].
The search and assessment strategies used in this review were based on course material from the DIRAC course of Systematic reviews and Meta Analysis held in Copenhagen in August 2007 [6]. However, as the aim was not to perform a meta-analysis and a thorough rating of the evidence, only one researcher did the searching and primary assessments. First author (TLG) did all the searches and assessing and discussed any doubts with the rest of the research team. Further, all results were scrutinised by the research group.
The search term "Type 2 Diabetes" was chosen above "Diabetes Mellitus" to fulfil the aim of this review, which does not consider "Type 1 Diabetes". Even though the Mesh term "Type 2 Diabetes" is relatively new, it realised papers published between 1994 and 2005. One unpublished study was considered for inclusion, based on published work concerning the methodology of the study. However, correspondence with the research team running the trial was inconclusive and left the study irrelevant for reviewing. Reviews that appeared in the searches were used in order to check the reference lists for includable randomized trials. The term "reminder system" was included as it was discovered that this term often covered what we defined as feedback. To distinguish between reminder system and feedback we assessed each of the retrieved papers separately.
The reference lists of the papers retrieved were checked for includable papers as were the "related articles" facility in PubMed. An initial database search retrieved six papers and a search of the related articles and reference list included an additional eight papers. Ten of the14 papers complied with the following inclusion criteria: • Randomised trial • Study concerning diabetes • Study set in general practice • Interventions aiming at using feedback to GPs on diabetes care.
The remaining four articles were excluded because they did not concern feedback.

Assessment
The included studies were assessed according to predefined criteria: • Aim of the study (How well did design cohere with study aim) • Method of evaluation (How well did methods of analysis cohere with study design?) • Format of feedback/intervention (Electronic or not) • Effect measure divided into:

Results
The ten papers presented ten different studies. Of these, six were conducted in USA, one in New Zealand, one in The Netherlands and two in Scandinavia. The papers were published between 1994 and 2005, of these two before 2000. The duration of the trials varied between two months and six years, with a median duration of 12 months. Table 1 summarizes the studies on design, number of participants, trial duration and data collection. The method of evaluation and effect measures are summarized in Table 2 and statistical significant effect measures are summarized in Table 3.

Aim of the studies
All studies aimed at improving the GPs' adherence to the diabetes guidelines in order to improve the care for PT2D. All the studies leaned on existing guidelines or developed guidelines as a part of the intervention.
Study design used to evaluate feedback varied according to whether the feedback was the single aim of evaluation, or the feedback was only part of a larger intervention with the aim of evaluating other means of quality improvement as well. Six study groups concentrated only on feedback in their interventions [9,10,[13][14][15][16]. Of these, one added benchmarks to the feedback in one intervention arm [16], and one let the patients fill in the feedback reports in the GP's waiting room [13].
Three studies compared regular feedback to other interventions, or combined feedback with other means of support: One combined feedback with outreach visits [8]; one compared feedback with face to face evaluation with an endocrinologist [7]. One study compared feedback filled in by patients in the waiting room and delivered in paper format with a computer reminder consisting of a blinking icon on the GP's computer screen [11].
One study categorised the intervention as multifaceted, and feedback to the GPs was part of the intervention [12].

Effect measures
All studies used process measures that were part of routine diabetes management, i.e. measuring blood glucose and serum cholesterol. Some used composite outcomes such as compliance rates, measuring the compliance of the GPs to the diabetes guidelines, while others focused on specific process or outcome measures ( Table 2).
One study differed from the others by using groups of endpoints defined as: PT2D satisfaction (PS), Diabetes specific quality of life (Dsql) and Depression severity symptoms (Dss) evaluated by using validated questionnaires [13]. These endpoints were based on questionnaires and process measures combined.

Data collection
Data were collected via chart review [9,10,15,16], encounter forms filled in by the participating GPs [8,11], databases [14], or by combining the methods [10,11]. In one study, all included patients were examined by one data collecting member of the research team [7].

Long term effects
Our searches revealed 3 interventions which lasted more than three years [7,12,16]. All three interventions showed significant positive results. In one trial, the researchers concentrated on process measures. They showed significant results on foot examination, Hba1c measurement and influenza vaccination [16]. The two other trials both included effect measures, and both showed significant improvements on Hba1c levels, serum cholesterol levels and blood pressure levels [7,12]. One long term trial included effect measures such as mortality, diabetic retinopathy, AMI, stroke, angina pectoris, claudicatio and amputation, but did not manage to show significant changes on any of these measures over a period of six years.

Methodological problems identified
In two studies, the participating GPs all worked in the same health facility [7,10]. This may have produced a spill-over effect. There was a profound sampling variation in the included studies, for example: One study group chose to set up inclusion criteria for the GPs' participation in the study [9]. Another study group invited the participating GPs through ads in newspapers [8]. In one study, only 5% of the invited GPs participated in the study [13]. This variation in sampling makes comparison between the included studies difficult and meta-analysis irrelevant.
All studies were un-blinded to participating doctors, as allocation concealment was not possible. Some attempts of blinding were made in one study [17]. However, three study groups did anticipate the problem of contamination between intervention and control groups. One performed statistical analysis to investigate the size of the problem, which was seemingly insignificant [7]. Another study group argued against contamination due to lack of blinding in the study, based on recorded differences between control an intervention group, but without performing any statistical analysis of the size of the problem [8].
Lastly, one study group, as mentioned above, attempted blinding. However, the researchers themselves argue in the paper that the blinding was not extensive enough.

Electronic feedback
Two trials complied with the definition of using electronic feedback [14,15]. Both trials obtained statistical significant effects on single measurements: Cholesterol measurement and blood pressure level, respectively. In addition, one of the trials demonstrated a statistical significant improvement of the compliance rate (Table 3).

Main findings
This review demonstrates that it seems possible to improve the quality of diabetes care using feedback to the GPs. Significant positive changes are primarily seen on process, but also on outcome of Type 2 diabetes care. In many studies, large numbers of effect measures showed no significant change, but no study groups report deterioration in effect measures. In table 2 effect measures which showed significant positive changes are marked. All of the included studies leaned on national diabetes guidelines or developed diabetes guidelines for good control and care within the study.

Implications of findings
The findings of this review indicate that feedback could be a valuable asset in quality improvement efforts. In the 2006 Cochrane Review referred to earlier in this paper, it was stated that "(...) the relative effectiveness of audit and feedback is likely to be greater when baseline adherence to recommended practice is low (...)" [3]. The results of this review support that statement to a certain extent: Among the endpoints reviewed, three endpoints showed significant improvement in more than one trial, namely numbers of foot examination made and the mean level of Hba1c and blood pressure. Foot examination is traditionally an endpoint with low guideline adherence. Mean level of Hba1c and blood pressure are influenced by life style changes and medication alterations, and so is very dependent on a strong commitment in the patient to alter their life style. Often, the strong dependency on life style changes can be unappealing to the doctors, because motivating the patient for life style changes is a difficult path to embark on [18].

Strengths and weaknesses
The strength of this review is the specific aim limiting the searches to include only feedback trials on diabetes care in general practice. Ideally, this would optimise the homogeneity of the studies and strengthen the conclusions of the review.
One weakness was the risk of missing important trials. Papers written in other languages than English were excluded and it has been reported that such exclusion of trials in systematic reviews increases the likelihood of systematic errors and reduces precision [19].
It was not possible to perform meta-analysis on the findings due to heterogeneity of the studies included: The designs and methods of feedback were too inconsistent and the endpoints measured and the duration of the trials varied too much. The aim of all studies included however, was to improve diabetes care in general practice, according to the relevant guidelines. This common goal, paired with the delivering of feedback to GPs in all the studies included makes it relevant to draw conclusions based on this review.

Delivering feedback
Clinicians have limited time to concentrate on quality improvement in daily practice which is why efforts to improve and sustain quality should be made as easily available and useable as possible [20]. Using computers is generally considered to be a positive thing saving time to the daily routines for GPs [21,22]. Considering this, it is striking that so few trials have tested electronic feedback on diabetes care in general practice.

Evaluating feedback
An important point when evaluating research within the field of quality improvement is choosing the relevant effect measures [18]. The studies included in this review were not consistent in choosing effect measures. Phillips [7] Pre-and post intervention mean group differences on patients in intervention vs. control groups. †Mean Hba1c.

Mean Ldl
Cholesterol. Blood pressure. Sequist [14] Both summary and individual composite endpoints †Cholesterol measured, Hba1c measured. Eye exam. ACE inh if hypertension. †Odds of receiving recommended diabetes care * Summary endpoint: diabetes reminders resulting in action/diabetes reminders in total Individual endpoints: No. of appropriate diabetes health services received by pt/total no. of diabetes health services pt Frijling [8] Mean compliance rate for each performance indicator at baseline and the mean change from baseline. †Foot exam. †Eye exam. BMI. Medication. Measured blood press. Anti diabetic treatment. Scheduled next appointment Lobach [9] Mean compliance rate for each performance indicator at baseline and the mean change from baseline.  [11] Was/not tested for blood glucose if eligible. †Blood glucose measured Kiefe [16] Proportional changes in the receiving of guideline specific diabetic services. †Influenza vac. †Foot exam. †Hba1c measured, cholesterol measured. Triglycerides measured de Fine Olivarius [12] Pre-and post intervention mean group differences on patients in intervention vs. control groups. Another issue is whether the changes detected in the effect measures are actually attributable to feedback. In this paper we included one obvious multifaceted intervention [12]. While multifaceted interventions certainly have their place in investigating quality improvement in diabetic care, it can be difficult to know exactly which efforts made the difference. We are aware that attributing the significant changes in the care of the PT2D in the included multifaceted intervention solely to the efforts of providing feedback to the GPs probably is an over-interpretation. However, the effort of providing GPs with continuous feedback was made, and therefore the intervention should be considered in this review.
In this study we have limited our search to randomized controlled trials (RCTs). This approach is debatable. One could argue that, while RCTs are often referred to as the gold standard of trial designs, it provides a one-shot effect, which often covers a short time frame of the patients medical history. It is evident, when researching within the field of chronic disease management, that long term effects of interventions are very relevant. However, follow-up over time and without specific interventions demonstrates huge improvements in diabetic care [23]. Thus, it is difficult in non-RCTs to be sure that the improvement in care is due to the specific intervention applied. Within the field of feedback on diabetes care to general practitioners, non-RCT long term effect research has revealed effects on process, outcome and the overall provision of diabetes care [24,25]. Even though these studies have not been included in this review due to design choices made, the results still relevantly support the conclusion that feedback on diabetes care to general practitioners can lead to better quality of care, and that this improvement of care could possibly be long term.

Conclusion
We found that disease specific feedback to GPs has an effect on diabetes care in General Practice. Pointing out which effect measures that are mostly affected by the interventions proved difficult.