Cross-sectional versus sequential quality indicators of risk factor management in patients with type 2 diabetes

A retrospective cohort study of a community-based primary care program's effects on pharmacotherapy quality in low-income Peruvians with type 2 diabetes and hypertension

Little is known about the effects of the Chronic Care Model (CCM) and community health workers (CHWs) on pharmacotherapy of type 2 diabetes and hypertension in resource-poor settings. This retrospective cohort implementation study evaluated the effects of a community-based program consisting of CCM, CHWs, guidelines-based treatment protocols, and inexpensive freely accessible medications on type 2 diabetes and hypertension pharmacotherapy quality. A door-to-door household survey identified 856 adults 35 years of age and older living in a low-income Peruvian community, of whom 83% participated in screening for diabetes and hypertension. Patients with confirmed type 2 diabetes and/or hypertension participated in the program's weekly to monthly visits for < = 27 months. The program was implemented as two care periods employed sequentially. During home care, CHWs made weekly home visits and a physician made treatment decisions remotely. During subsequent clinic care, a physician attended patients in a centralized clinic. The study compared the effects of program (pre- versus post-) (N = 262 observations), and home versus clinic care periods (N = 211 observations) on standards of treatment with hypoglycemic and antihypertensive agents, angiotensin converting enzyme inhibitors, and low-dose aspirin. During the program, 80% and 50% achieved hypoglycemic and antihypertensive standards, respectively, compared to 35% and 8% prior to the program, RRs 2.29 (1.72-3.04, p <0.001) and 6.64 (3.17-13.9, p<0.001). Achievement of treatment standards was not improved by clinic compared to home care (RRs 1.0 +/- 0.08). In both care periods, longer retention in care (>50% of allowable time) was associated with achievement of all treatment standards. 85% compared to 56% achieved the hypoglycemic treatment standard with longer and shorter retention, respectively, RR 1.52 (1.13-2.06, p<0.001); 56% compared to 27% achieved the antihypertensive standard, RR 2.11 (1.29-3.45, p<0.001). In a dose-dependent manner, the community-based program was associated with improved guidelines-based pharmacotherapy of type 2 diabetes and hypertension.

Quality criteria/key components for high quality of diabetes management to avoid diabetes-related complications

Aim

The aim of this review shoud be to map data and to identify quality indicators for good practices for diabetes management and secondary prevention, specifically of type 2 diabetes.

Methods

To achieve this aim we performed the following steps: (i) a literature review on evaluation criteria, (ii) selection of quality criteria and key components for high quality of care, (iii) creation of a checklist to identify the best practice of diabetes management based on the detected criteria.

Results

The literature search about the quality indicators for diabetes care resulted in the following: identifying of key components and quality indicators for structure, process and outcome quality.

Conclusions

The set of quality criteria will be discussed and used to identify the best practice diabetes management programs for secondary prevention of type 2 diabetes.

Prescribing quality in secondary care patients with different stages of chronic kidney disease: a retrospective study in the Netherlands

OBJECTIVES

Insight in the prescribing quality for patients with chronic kidney disease (CKD) in secondary care is limited. The aim of this study is to assess the prescribing quality in secondary care patients with CKD stages 3-5 and possible differences in quality between CKD stages.

DESIGN

This was a retrospective cohort study.

SETTING

Data were collected at two university (n=569 and n=845) and one non-university nephrology outpatient clinic (n=1718) in the Netherlands.

PARTICIPANTS

Between March 2015 and August 2016, data were collected from patients with stages 3a-5 CKD seen at the clinics. Blood pressure measurements, laboratory measurements and prescription data were extracted from medical records. For each prescribing quality indicator, patients with incomplete data required for calculation were excluded.

OUTCOME MEASURES

Potentially appropriate prescribing of antihypertensives, renin-angiotensin-aldosterone system (RAAS) inhibitors, statins, phosphate binders and potentially inappropriate prescribing according to prevailing guidelines was assessed using prescribing quality indicators. Χ² or Fisher's exact tests were used to test for differences in prescribing quality.

RESULTS

RAAS inhibitors alone or in combination with diuretics (57% or 52%, respectively) and statins (42%) were prescribed less often than phosphate binders (72%) or antihypertensives (94%) when indicated. Active vitamin D was relatively often prescribed when potentially not indicated (19%). Patients with high CKD stages were less likely to receive RAAS inhibitors but more likely to receive statins when indicated than stage 3 CKD patients. They also received more active vitamin D and erythropoietin-stimulating agents when potentially not indicated.

CONCLUSIONS

Priority areas for improvement of prescribing in CKD outpatients include potential underprescribing of RAAS inhibitors and statins, and potential overprescribing of active vitamin D. CKD stage should be taken into account when assessing prescribing quality.

Toward Standardized Monitoring of Patients With Chronic Diseases in Primary Care Using Electronic Medical Records: Systematic Review

Background

Long-term care for patients with chronic diseases poses a huge challenge in primary care. In particular, there is a deficit regarding monitoring and structured follow-up. Appropriate electronic medical records (EMRs) could help improving this but, so far, there are no evidence-based specifications concerning the indicators that should be monitored at regular intervals.

Objective

The aim was to identify and collect a set of evidence-based indicators that could be used for monitoring chronic conditions at regular intervals in primary care using EMRs.

Methods

We searched MEDLINE (Ovid), Embase (Elsevier), the Cochrane Library (Wiley), the reference lists of included studies and relevant reviews, and the content of clinical guidelines. We included primary studies and guidelines reporting about indicators that allow for the assessment of care and help monitor the status and process of disease for five chronic conditions, including type 2 diabetes mellitus, asthma, arterial hypertension, chronic heart failure, and osteoarthritis.

Results

The use of the term “monitoring” in terms of disease management and long-term care for patients with chronic diseases is not widely used in the literature. Nevertheless, we identified a substantial number of disease-specific indicators that can be used for routine monitoring of chronic diseases in primary care by means of EMRs.

Conclusions

To our knowledge, this is the first systematic review summarizing the existing scientific evidence on the standardized long-term monitoring of chronic diseases using EMRs. In a second step, our extensive set of indicators will serve as a generic template for evaluating their usability by means of an adapted Delphi procedure. In a third step, the indicators will be summarized into a user-friendly EMR layout.

Development and validation of prescribing quality indicators for patients with type 2 diabetes

AIM

Quality indicators are used to measure whether healthcare professionals act according to guidelines, but few indicators focus on the quality of pharmacotherapy for diabetes. The aim of this study was to develop and validate a set of prescribing quality indicators (PQIs) for type 2 diabetes in primary care, and to apply this set in practice. To take into account the stepwise treatment of chronic disease, clinical action indicators were specifically considered.

METHODS

Potential PQIs were derived from clinical practice guidelines and evaluated using the RAND/UCLA Appropriateness Method, a modified Delphi panel. Thereafter, the feasibility of calculating the PQIs was tested in two large Dutch primary care databases including >80 000 diabetes patients in 2012.

RESULTS

32 PQIs focusing on treatment with glucose, lipid, blood pressure and albuminuria lowering drugs, and on vaccination, medication safety and adherence were assessed by ten experts. After the Delphi panel, the final list of twenty PQIs was tested for feasibility. All PQIs definitions were feasible for measuring the quality of medication treatment using these databases. Indicator scores ranged from 18.8% to 90.8% for PQIs focusing on current medication use, clinical action and medication choice, and from 2.1% to 37.2% for PQIs focusing on medication safety.

DISCUSSION AND CONCLUSIONS

Twenty PQIs focusing on treatment with glucose, lipid, blood pressure and albuminuria lowering drugs, and on medication safety in type 2 diabetes were developed, considered valid and operationally feasible. Results showed room for improvement, especially in initiation and intensification of treatment as measured with clinical action indicators.

Process quality indicators for chronic kidney disease risk management: a systematic literature review

BACKGROUND AND OBJECTIVES

Quality indicators (QIs) can be used for measuring the quality of actions of healthcare providers. This systematic review gives an overview of such QIs measuring processes of care for chronic kidney disease (CKD), and identifies the QIs that have content, face, operational and/or predictive validity.

METHODS

PubMed and Embase were searched using a strategy combining the terms "quality of care," "quality indicators" and "chronic kidney disease". Papers were included if they focused on developing, testing or applying QIs for assessing the quality of care in adult patients with CKD not on renal replacement therapy.

RESULTS

Two hundred and seventy-three QIs from thirty-one papers were extracted, including QIs on adequate monitoring of kidney function and vascular risk factors, on indicated treatment, drug safety, adherence and referral to a specialist. The QIs that were considered content, face and operational valid focused on monitoring of glomerular filtration rate, albumin-creatinine ratio, lipid levels and blood pressure, the use of non-steroidal anti-inflammatory drugs, nitrofurantoin and biphosphonates in patients with CKD, and QIs on monitoring haemoglobin and treatment with angiotensin-converting-enzyme-inhibitors/angiotensin-receptor-II-blockers in patients with CKD and comorbidities. No QIs were tested for predictive validity. In addition, only two QIs focused on diet and no other QIs focused on lifestyle management.

CONCLUSIONS

Based on this review, sufficiently validated QIs can be selected for measuring the quality of CKD care. This review provides insight in QIs that need further validation, and in areas of care where QIs are still lacking.

Clinical action measures improve the reliability of feedback on quality of care in diabetes centres: a retrospective cohort study

Background

Assessment of quality of care using classical threshold measures (TM) is open to debate. Measures that take into account the clinician’s actions and the longitudinal nature of chronic care are more reliable, although their major limitation is that they require more sophisticated electronic health records. We created a clinical action measure (CAM) for the control of LDL and non-HDL cholesterol from low-complexity data, and investigated how quality of care in individual diabetes centres based on the CAM is related to that based on the classical TM.

Methods

Data was used from 3421 diabetes patients treated in 95 centres, collected in two consecutive retrospective data collections. Patients met the TM when their index value was below target. Patients met the CAM when their index value was below target or above target but for whom treatment initiation or intensification, or possible contraindication, was indicated.

Results

Based on the TM, 60–70 % of the patients received good care. This percentage increased significantly using the CAM (+5 %, p < 0.001). At the centre level, the CAM was associated with a higher median score, and a change in position among centres (‘poor’, ‘good’ or ‘excellent’ performer) for 5–10 % of the centres.

Conclusions

Judging quality of diabetes care of a centre based on a TM may be misleading. Low-complexity data available from a quality improvement initiative can be used to construct a more fair and feasible measure of quality of care.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-016-1670-5) contains supplementary material, which is available to authorized users.

Episode-Based Approaches to Measuring Health Care Quality

Most currently available quality measures reflect point-in-time provider tasks, providing a limited and fragmented assessment of care. The concept of episodes of care could be used to develop quality measurement approaches that reflect longer periods of care. With input from clinical experts, we constructed episode-of-care frameworks for six illustrative conditions and identified potential gaps and measure development priority areas. Episode-based measures could assess changes in health outcomes ("delta measures"), the amount of time during an episode in which a patient has suboptimal health status ("integral measures"), quality contingent upon events occurring previously ("contingent measures"), and composites of measures throughout the episode. This article identifies a number of challenges that will need to be addressed to advance operationalization of episode-based quality measurement.

Potential overtreatment and undertreatment of diabetes in different patient age groups in primary care after the introduction of performance measures

OBJECTIVE

To assess whether after the introduction of diabetes performance measures decreases in undertreatment correspond with increases in overtreatment for blood pressure (BP) and glycemic control in different patient age groups.

RESEARCH DESIGN AND METHODS

We conducted a cohort study using data from the Groningen Initiative to Analyse Type 2 Diabetes Treatment (GIANTT) database. General practices were included when data were available from 1 year before to at least 1 year after the introduction of diabetes performance measures. Included patients had a confirmed diagnosis of type 2 diabetes. Potential overtreatment was defined as prescribing maximum treatment or a treatment intensification to patients with a sustained low-risk factor level. Potential undertreatment was defined as a lack of treatment intensification in patients with a sustained high-risk factor level. Percentages of over- and undertreated patients at baseline were compared with those in subsequent years, and stratified analyses were performed for different patient age groups.

RESULTS

For BP, undertreatment significantly decreased from 61 to 57% in the first year after the introduction of performance measures. In patients >75 years of age, undertreatment decreased from 65 to ∼61%. Overtreatment was relatively stable (∼16%). For glycemic control, undertreatment significantly increased from 49 to 53%, and overtreatment remained relatively stable (∼7%).

CONCLUSIONS

The improvement of BP undertreatment after introduction of the performance measures did not correspond with an increase in overtreatment. The performance measures appeared to have little impact on improving glucose-regulating treatment. The trends did not differ among patient age groups.

Do treatment quality indicators predict cardiovascular outcomes in patients with diabetes?

Background

Landmark clinical trials have led to optimal treatment recommendations for patients with diabetes. Whether optimal treatment is actually delivered in practice is even more important than the efficacy of the drugs tested in trials. To this end, treatment quality indicators have been developed and tested against intermediate outcomes. No studies have tested whether these treatment quality indicators also predict hard patient outcomes.

Methods

A cohort study was conducted using data collected from >10.000 diabetes patients in the Groningen Initiative to Analyze Type 2 Treatment (GIANTT) database and Dutch Hospital Data register. Included quality indicators measured glucose-, lipid-, blood pressure- and albuminuria-lowering treatment status and treatment intensification. Hard patient outcome was the composite of cardiovascular events and all-cause death. Associations were tested using Cox regression adjusting for confounding, reporting hazard ratios (HR) with 95% confidence intervals.

Results

Lipid and albuminuria treatment status, but not blood pressure lowering treatment status, were associated with the composite outcome (HR = 0.77, 0.67–0.88; HR = 0.75, 0.59–0.94). Glucose lowering treatment status was associated with the composite outcome only in patients with an elevated HbA1c level (HR = 0.72, 0.56–0.93). Treatment intensification with glucose-lowering but not with lipid-, blood pressure- and albuminuria-lowering drugs was associated with the outcome (HR = 0.73, 0.60–0.89).

Conclusion

Treatment quality indicators measuring lipid- and albuminuria-lowering treatment status are valid quality measures, since they predict a lower risk of cardiovascular events and mortality in patients with diabetes. The quality indicators for glucose-lowering treatment should only be used for restricted populations with elevated HbA1c levels. Intriguingly, the tested indicators for blood pressure-lowering treatment did not predict patient outcomes. These results question whether all treatment indicators are valid measures to judge quality of health care and its economics.

Association between performance measures and glycemic control among patients with diabetes in a community-wide primary care cohort

BACKGROUND

Performance measures are used for assessing quality of care. Higher performance shown by these measures is expected to reflect better care, but little is known whether they predict better patient outcomes.

OBJECTIVE

To assess the predictive value of performance measures of glucose management on glycemic control, and evaluate the impact of patient characteristics on this association.

RESEARCH DESIGN

Cohort study (2007-2009).

SUBJECTS

A total of 15,454 type 2 diabetes patients (mean age, 66.5 y; 48% male) from the GIANTT cohort.

MEASURES

We included performance measures assessing frequency of HbA1c monitoring, glucose-lowering treatment status, and treatment intensification. Associations between performance and glycemic control were tested using multivariate linear regression adjusted for confounding, reporting estimated differences in HbA1c with 95% confidence intervals (CI). Impact of patient characteristics was examined through interactions.

RESULTS

Annual HbA1c monitoring was associated with better glycemic control when compared with no such monitoring (HbA1c -0.29%; 95% CI -0.37, -0.22). This association lost significance in patients with lower baseline HbA1c, older age, and without macrovascular comorbidity. Treatment status was associated with better glycemic control only in patients with elevated baseline HbA1c. Treatment intensification after elevated HbA1c levels was associated with better glycemic control compared with no intensification (HbA1c -0.21; 95% CI -0.26, -0.16).

CONCLUSIONS

Performance measures of annual HbA1c monitoring and of treatment intensification did predict better patient outcomes, whereas the measure of treatment status did not. Predictive value of annual monitoring and of treatment status varied across patient characteristics, and it should be used with caution when patient characteristics cannot be taken into account.

Selecting clinical quality indicators for laboratory medicine

BACKGROUND

Quality in laboratory medicine is often described as doing the right test at the right time for the right person. Laboratory processes currently operate under the oversight of an accreditation body which gives confidence that the process is good. However, there are aspects of quality that are not measured by these processes. These are largely focused on ensuring that the most clinically appropriate test is performed and interpreted correctly.

METHODS

Clinical quality indicators were selected through a two-phase process. Firstly, a series of focus groups of clinical scientists were held with the aim of developing a list of quality indicators. These were subsequently ranked in order by an expert panel of primary and secondary care physicians.

RESULTS

The 10 top indicators included the communication of critical results, comprehensive education to all users and adequate quality assurance for point-of-care testing. Laboratories should ensure their tests are used to national standards, that they have clinical utility, are calibrated to national standards and have long-term stability for chronic disease management. Laboratories should have error logs and demonstrate evidence of measures introduced to reduce chances of similar future errors. Laboratories should make a formal scientific evaluation of analytical quality.

CONCLUSIONS

This paper describes the process of selection of quality indicators for laboratory medicine that have been validated sequentially by deliverers and users of the service. They now need to be converted into measureable variables related to outcome and validated in practice.

Development of a minimal set of prescribing quality indicators for diabetes management on a general practice level

OBJECTIVE

To identify the relevant prescribing quality domains of type 2 diabetes mellitus care as a basis for the selection of a minimal set of prescribing quality indicators from a set of previously validated indicators.

METHODS

We used the principal factor analysis to identify the underlying dimensions or domains of prescribing quality for 76 general practitioners participating to the Groningen Initiative to Analyse Type 2 Diabetes Treatment project in the Netherlands. From a set of 10 prescribing quality indicators covering various aspects of cardiovascular and metabolic management, we selected a subset of indicators with the highest loading within each identified domain. Next, we evaluated the effect of using this subset on the quintile ranking of practices on their prescribing quality scores.

RESULTS

We identified five prescribing quality domains in our data set: two assessing initiation of pharmacotherapy for different risk factors in diabetic patients, two on stepwise intensification of treatment, and one on treatment of patients with cardiovascular disease. A composite score comprising the indicators selected from each of the domains showed good agreement with the composite score comprising all indicators with 82% of general practitioners either not changing their position or shifting their ranking by only one quintile.

CONCLUSIONS

We showed that a minimal set of prescribing quality indicators for type 2 diabetes mellitus care should not just focus on the management of different clinical risk factors but also reflect different steps of treatment intensification. The results of our study are relevant for stakeholders when selecting quality indicators to assess the quality of prescribing in diabetic patients.

Do we need individualised prescribing quality assessment? The case of diabetes treatment

Prescribing quality assessment is increasingly used in improvement programs and pay-for-performance policies. Within the area of diabetes many quality indicators have been developed. Some measure prescribing on a general level, e.g. calculating percentages of patients prescribed any statins. Others are very specific, e.g. percentages of patients with an elevated LDL-cholesterol in whom lipid-lowering treatment is started unless contraindicated or return to control within 3 months. Although the latter seems more precise, we question how far one should go in developing such indicators. Using the example of diabetes treatment, we highlight the need, opportunities, and feasibility of assessing prescribing quality in the context of individualised treatment. We conclude that it is not realistic to develop indicators that take all possible aspects of therapy non-response, intolerance and patient preferences into account. We do recommend further development of indicators that better address subpopulations in need of adjusted treatment, such as elderly or patients with comorbidity.

Review: relation between quality-of-care indicators for diabetes and patient outcomes: a systematic literature review

The authors conducted a systematic literature review to assess whether quality indicators for diabetes care are related to patient outcomes. Twenty-four studies were included that formally tested this relationship. Quality indicators focusing on structure or processes of care were included. Descriptive analyses were conducted on the associations found, differentiating for study quality and level of analysis. Structure indicators were mostly tested in studies with weak designs, showing no associations with surrogate outcomes or mixed results. Process indicators focusing on intensification of drug treatment were significantly associated with better surrogate outcomes in three high-quality studies. Process indicators measuring numbers of tests or visits conducted showed mostly negative results in four high-quality studies on surrogate and hard outcomes. Studies performed on different levels of analysis and studies of lower quality gave similar results. For many widely used quality indicators, there is insufficient evidence that they are predictive of better patient outcomes.

Identifying targets to improve treatment in type 2 diabetes; the Groningen Initiative to aNalyse Type 2 diabetes Treatment (GIANTT) observational study

PURPOSE

Assessment of quality of cardiometabolic risk management in diabetes in primary care.

METHODS

In a descriptive cohort study including 95 Dutch general practices, we assessed medication treatment in relation to the level of control for HbA1c, systolic blood pressure (SBP) and LDL-cholesterol (LDL-c) in 2007. We also applied a prospective measure of treatment quality by assessing treatment modifications in not well-controlled patients. In a subpopulation of 23 practices, we studied trends in these quality indicators from 2004 (2059 patients) to 2007 (2929 patients).

RESULTS

In 2007, averages for HbA1c, SBP and LDL-c were 6.9%, 142 mmHg and 2.3 mmol/l, respectively. Of the patients with an HbA1c >  8.5%, 16% were treated with one oral drug class and 50% used insulin. In 27% of these patients, therapy modification occurred subsequently. During the 4-year period, a slight decrease in average HbA1c was observed, but no changes in treatment level. In 2007, 56% of the patients had an SBP ≥ 140 mmHg, 19% of whom were not using antihypertensives. In the 13% with an SBP > 160 mmHg, 23% received a therapy modification. During the 4-year period, the average SBP decreased with 6 mmHg but the treatment level showed no substantial increase. In 2007, 39% had an LDL-c level ≥ 2.5 mmol/l, 49% of whom were not using statins. Of the patients with an LDL-c > 3.5 mmol/l, only 9% received a therapy modification.

CONCLUSIONS

The decreasing population averages of HbA1c, SBP and LDL-c values suggest improvement in quality of care. However, the relatively few therapy modifications observed in insufficiently controlled patients show room for improvement.

Exploring and comparing the characteristics of nonlatent and latent composite scores: implications for pay-for-performance incentive design

A concise and reliable composite quality score would be helpful in judging the quality of a hospital's services, especially for pay-for-performance (P4P) initiatives. This study compared several nonlatent and latent composite quality scores to evaluate the quality of care using diabetes mellitus (DM) P4P data and discusses their characteristics and implications for P4P policy. The authors describe a cross-sectional study of the DM P4P data collected from the claims data of the Bureau of National Health Insurance (NHI) in Taiwan from January 2007 to December 2007. The DM patient outcome data, such as hemoglobin A1C values, were retrieved from the P4P database sponsored by the Bureau of NHI in Taiwan. The composite scores were derived from the following methods: 1) nonlatent scores methods (e.g., the raw sum score and the all-or-none score methods)and 2) latent scores methods (e.g., item-response theory-based Models I and II and the PRIDIT model). These scores are compared in terms of 2 aspects-agreement of hospital rankings (using Spearman's rank correlation) and reliability (using bootstrap methods). The latent methods were superior to the nonlatent methods because they were more reliable and had specific weighting themes. The correlations among the 3 latent methods were moderately high. The use of the PRIDIT approach, which is moderately difficult compared with item response theory-based model, is recommended if the insurer wants to balance convenience and precision.

A systematic literature review: prescribing indicators related to type 2 diabetes mellitus and cardiovascular risk management

PURPOSE

Valid prescribing indicators (PI) are needed for reliable assessment of prescribing quality. The purpose of this study is to describe the validity of existing PI for type 2 diabetes mellitus and cardiovascular risk management.

METHODS

We conducted a systematic literature search for studies describing the development and assessment of relevant PIs between January 1990 and January 2009. We grouped identified PI as drug- or disease-oriented, and according to the aspects of prescribing addressed and the additional clinical information included. We reviewed the clinimetric characteristics of the different types of PI.

RESULTS

We identified 59 documents describing the clinimetrics of 16 types of PI covering relevant prescribing aspects, including first-choice treatment, safety issues, dosing, costs, sufficient and timely treatment. We identified three types of drug-oriented, and five types of disease-oriented PI with proven face and content validity as well as operational feasibility in different settings. PI focusing on treatment modifications were the only indicators that showed concurrent validity. Several solutions were proposed for dealing with case-mix and sample size problems, but their actual effect on PI scores was insufficiently assessed. Predictive validity of individual PI is not yet known.

CONCLUSION

We identified a range of existing PI that are valid for internal quality assessment as they are evidence-based, accepted by professionals, and reliable. For external use, problems of patient case-mix and sample size per PI should be better addressed. Further research is needed for selecting indicators that predict clinical outcomes.

Methods to identify the target population: implications for prescribing quality indicators

Background

Information on prescribing quality is increasingly used by policy makers, insurance companies and health care providers. For reliable assessment of prescribing quality it is important to correctly identify the patients eligible for recommended treatment. Often either diagnostic codes or clinical measurements are used to identify such patients. We compared these two approaches regarding the outcome of the prescribing quality assessment and their ability to identify treated and undertreated patients.

Methods

The approaches were compared using electronic health records for 3214 diabetes patients from 70 general practitioners. We selected three existing prescribing quality indicators (PQI) assessing different aspects of treatment in patients with hypertension or who were overweight. We compared population level prescribing quality scores and proportions of identified patients using definitions of hypertension or being overweight based on diagnostic codes, clinical measurements or both.

Results

The prescribing quality score for prescribing any antihypertensive treatment was 93% (95% confidence interval 90-95%) using the diagnostic code-based approach, and 81% (78-83%) using the measurement-based approach. Patients receiving antihypertensive treatment had a better registration of their diagnosis compared to hypertensive patients in whom such treatment was not initiated. Scores on the other two PQI were similar for the different approaches, ranging from 64 to 66%. For all PQI, the clinical measurement -based approach identified higher proportions of both well treated and undertreated patients compared to the diagnostic code -based approach.

Conclusions

The use of clinical measurements is recommended when PQI are used to identify undertreated patients. Using diagnostic codes or clinical measurement values has little impact on the outcomes of proportion-based PQI when both numerator and denominator are equally affected. In situations when a diagnosis is better registered for treated than untreated patients, as we observed for hypertension, the diagnostic code-based approach results in overestimation of provided treatment.

Improving hypertension quality measurement using electronic health records

BACKGROUND

Simple hypertension outcome measures may not indicate which patients receive poor care. This could be problematic as incentives increase.

OBJECTIVE

Compare measured quality using simple outcome measures to more sophisticated measures utilizing data available within an electronic health record.

DESIGN

Cross-sectional study.

SUBJECTS

A total of 5905 hypertensive adults with 3 or more clinic visits between July 1, 2005 and December 31, 2006 at an internal medicine clinic.

MEASURES

We measured simple control as the proportion of diagnosed hypertension patients with their last blood pressure below goal (<140/90 mm Hg or <130/80 if diabetic). We compared this to sequentially more complex measures.

RESULTS

Among nondiabetic patients, baseline measurement of control was 58.1% [95% confidence interval (CI), 56.5-59.6]. Counting patients as having adequate care whose last or mean blood pressure was at or below goal raised performance to 75.4%. Accounting for patients prescribed aggressive treatment raised it to 82.5%. Accounting for low diastolic blood pressure raised it to 83.6%. Including patients with undiagnosed hypertension lowered it to 80.5%. For diabetes patients, baseline measurement of control was 29.9% (95% CI, 27.6-32.3) and changed to 46.4%, 72.8%, 76.7%, and 73.6%, respectively.

CONCLUSIONS

It is possible to use electronic health record data to devise hypertension measures that may better reflect who has actionable uncontrolled blood pressure, do not penalize clinicians treating resistant hypertension patients, reduce the encouragement of potentially unsafe practices, and identify patients possibly receiving poor care with no hypertension diagnosis. This could improve the detection of true quality problems and remove incentives to over treat or stop caring for patients with resistant hypertension.

Treatment intensification and risk factor control: toward more clinically relevant quality measures

BACKGROUND

Intensification of pharmacotherapy in persons with poorly controlled chronic conditions has been proposed as a clinically meaningful process measure of quality.

OBJECTIVE

To validate measures of treatment intensification by evaluating their associations with subsequent control in hypertension, hyperlipidemia, and diabetes mellitus across 35 medical facility populations in Kaiser Permanente, Northern California.

DESIGN

Hierarchical analyses of associations of improvements in facility-level treatment intensification rates from 2001 to 2003 with patient-level risk factor levels at the end of 2003.

PATIENTS

Members (515,072 and 626,130; age >20 years) with hypertension, hyperlipidemia, and/or diabetes mellitus in 2001 and 2003, respectively.

MEASUREMENTS

Treatment intensification for each risk factor defined as an increase in number of drug classes prescribed, of dosage for at least 1 drug, or switching to a drug from another class within 3 months of observed poor risk factor control.

RESULTS

Facility-level improvements in treatment intensification rates between 2001 and 2003 were strongly associated with greater likelihood of being in control at the end of 2003 (P < or = 0.05 for each risk factor) after adjustment for patient- and facility-level covariates. Compared with facility rankings based solely on control, addition of percentages of poorly controlled patients who received treatment intensification changed 2003 rankings substantially: 14%, 51%, and 29% of the facilities changed ranks by 5 or more positions for hypertension, hyperlipidemia, and diabetes, respectively.

CONCLUSIONS

Treatment intensification is tightly linked to improved control. Thus, it deserves consideration as a process measure for motivating quality improvement and possibly for measuring clinical performance.