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The ability to generate registries of patients with particular clinical attributes, such as diagnoses or medications taken, is central to measuring and improving the quality of health care. However, it is not known how many providers have the ability to generate such registries.
To assess the proportion of physician practices that can construct registries of patients with specific diagnoses, laboratory results, or medications, and to determine the relationship between electronic health record (EHR) usage and the ability to perform registry functions.
We conducted a mail survey of a stratified random sample of physician practices in Massachusetts in the northeastern United States (N = 1884). The survey included questions about the physicians’ ability to generate diagnosis, laboratory result, and medication registries; the presence of EHR; and usage of specific EHR features.
The response rate was 71% (1345/1884). Overall, 79.8% of physician practices reported being able to generate registries of patients by diagnosis; 56.1% by laboratory result; and 55.8% by medication usage. In logistic regression analyses, adjusting for urban/rural location, practice size and ownership, teaching status, hospital affiliation, and specialty, physician practices with an EHR were more likely to be able to construct diagnosis registries (adjusted odds ratio [OR] 1.53, 95% confidence interval [CI] 1.25 - 1.86), laboratory registries (OR 1.42, 95% CI 1.22 - 1.66), and medication registries (OR 2.30, 95% CI 1.96 - 2.70).
Many physician practices were able to generate registries, but this capability is far from universal. Adoption of EHRs appears to be a useful step toward this end, and practices with EHRs are considerably more likely to be able to carry out registry functions. Because practices need registries to perform broad-based quality improvement, they should consider adopting EHRs that have built-in registry functionality.
With the publication of the Institute of Medicine’s
Registries play a key part in the Chronic Care Model [
Laboratory result registries have been used for several purposes, but the most common is detection of patients overdue for screening tests [
Taken together, this evidence suggests that diagnosis, medication and laboratory registries are essential and effective tools for improving the quality and safety of health care at the population level. A variety of studies at different sites, using different registries and with different disease foci have shown positive results [
In order to understand better the registry generation capabilities of community ambulatory practices, as well as the relationship between EHR usage and registry capabilities, we undertook the present study. Our goal was to measure physicians’ general abilities to perform registry functions in office practice and to explore further the hypothesis that use of electronic health records is associated with the ability to perform registry functions. This study is one aim of a larger study which used a variety of methods, including surveys, focus groups, direct observation, and quality assessment. The goal of the larger study was to measure adoption and use of EHRs in Massachusetts and to compare state-wide adoption to three specific communities in the state that were in the process of implementing community-wide electronic health records with information exchange. Other results of the larger study have been have published previously [
We carried out a statewide survey of physician practices in Massachusetts between June 2005 and November 2005. We began with a commercial database of physicians in Massachusetts (Folio Associates, Hyannis, MA) which contained contact information for 20,704 physicians practicing at 6308 distinct practice sites in the state. We drew a stratified random sample of practice sites from this database and selected one physician at random from each practice. Our sample was stratified by geography (urban vs nonurban based on county designation, except in the case where there were rural ZIP codes in urban counties, where ZIP codes were used instead), practice size (1 physician, 2 - 3 physicians, 4 - 6 physicians, and 7 or more physicians, exclusive of residents), and practice type (hospital-based primary care, hospital-based specialty/mixed, non-hospital-based primary care, or non-hospital-based specialty/mixed). These sampling characteristics were based on values in the commercial database.
Practices in rural parts of Massachusetts, primary care practices within hospitals, and large practices were oversampled by 100% in our sampling plan to ensure we had adequate representation of these particular practice types. Further details of the sampling plan have been reported previously [
Ultimately, we identified a sample of 1884 physician practices across the state of Massachusetts. We mailed a randomly chosen physician at each practice the survey and a US $20 cash incentive to encourage participation. We contacted non-respondents by phone several times and also sent the survey to them two more times (without further cash incentive). The survey contained demographic questions (relating to practice size, teaching, and practice ownership), as well as a variety of questions about quality improvement, practice satisfaction, use of technology, and finances. Some of these questions have been analyzed as part of other aims of this study [
The survey also asked questions about the use of registry functions and availability of an EHR (defined as “an integrated clinical information system that tracks patient health data, and may include such functions as visit notes, prescriptions, lab orders, etc”) in the physician’s practice. Specifically, physicians were asked to rate the ease of creating lists of patients by diagnosis or health risk (eg, diabetes), by laboratory results (eg, patients with abnormal hematocrit levels), and by medications they currently take (eg, patients on warfarin), using a five-point scale: very easy, somewhat easy, somewhat difficult, very difficult, and cannot generate. Furthermore, physicians were asked if their practice had components of an EHR, specifically defined as “an integrated clinical information system that tracks patient health data, and may include such functions as visit notes, prescriptions, laboratory orders, etc” and were also surveyed on the availability and use of specific EHR components, such as structured problem or medication lists and electronic reporting and review of laboratory results. The survey instrument and study protocol were reviewed and approved by the Partners Healthcare Institutional Review Board (IRB). The instrument is available as an appendix to this article (See
We used SAS 9.1.3 (SAS Institute, Cary, NC), applying weights throughout our analysis to control for both our stratified sampling plan (which included over-sampling of specific groups) and for variable response rates in different strata (specialty, category of practice size, hospital affiliation, and urban/rural location). We used frequency weights (fweights) which are the inverse of the response proportion for each stratum or, equivalently, the weights were determined by taking the population size for each stratum divided by the number of responses. Conceptually, the fweight for a particular response corresponds to the number of physician practices in Massachusetts that this response represents. The ultimate purpose of this weighting strategy was to make our results representative of the population of ambulatory care physician practices in Massachusetts.
We used logistic regression to assess the relationship between the presence of electronic health records in the practice and the ability to create diagnosis registries, laboratory test registries, and medication registries, adjusting each model for the following potential confounding factors:
urban/rural location
practice size
practice ownership (owner, part-owner, non-owner)
teaching status (whether any students or residents were present in the past year)
hospital affiliation
practice type (chosen from solo primary care practice, solo specialty care practice, primary care group/partnership, single specialty group/partnership, multi-specialty group/partnership)
In a secondary analysis limited to practices that had EHRs, we used chi-square tests to examine the relationship between use of key EHR features and the ability to generate each type of registry (diagnosis, laboratory test, medication). For the feature-specific analysis we looked at the effect of problem list use on the ability to generate diagnosis registries, electronic laboratory result review on laboratory test registries, and electronic medication list use on medication registries. In each one of the three cases, the associated feature was chosen for analysis because it was the most directly related feature to the registry type.
A total of 1345 physicians (71%, 1345 of 1884) completed the survey, 1328 by mail and 17 by phone. There were no significant differences between respondents and non-respondents on the sampling characteristics (specialty, practice size, hospital affiliation, and rural practice). The practices reported using a wide variety of commercially available and self-developed EHR systems.
Among the 356 practices which had an EHR and reported its name, a total of 187 (52.5%) used one of the 4 most prevalent systems while the remaining 169 (47.5%) reported using one of 78 other systems that were named. There were also 31 practices that reported having an EHR but did not provide its name—they were still counted as having an EHR for purposes of the analysis.
Practice characteristics
n of practices | % of practices | ||
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Rural | 331 | 24.6 | |
Urban | 1014 | 75.4 | |
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≥ 6 physicians | 504 | 37.5 | |
3 - 5 physicians | 280 | 20.8 | |
1 - 2 physicians | 383 | 28.5 | |
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Full owner | 460 | 34.2 | |
Part owner | 172 | 12.8 | |
Non owner | 542 | 40.3 | |
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Involved in teaching | 552 | 41.0 | |
Not involved in teaching | 628 | 46.7 | |
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Hospital based practice | 360 | 26.8 | |
Non-hospital based practice | 974 | 72.4 | |
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Solo primary care practice | 154 | 11.4 | |
Solo specialty care practice | 192 | 14.3 | |
Primary care group/partnership | 309 | 23.0 | |
Single specialty group/partnership | 338 | 25.1 | |
Multi-specialty group/partnership | 177 | 13.2 | |
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Yes | 387 | 28.8 | |
No | 794 | 59.0 |
Overall, 79.8% of physicians reported that their practices could generate registries of patients with a particular diagnosis; 56.1% could generate registries of patients with a specific laboratory result; and 55.8% could generate registries of patients taking a particular medication. Among physicians who reported that their practices were able to generate registries, the reported ease with which such registries could be generated varied greatly, as shown in
Ease or difficulty of generating registries of patients based on diagnosis, laboratory result and medication usea
Ease or Difficulty | Diagnosis registry | Laboratory result registry | Medication registry |
Very Easy | 15.0% | 6.5% | 7.4% |
Somewhat Easy | 23.9% | 8.0% | 10.4% |
Somewhat Difficult | 21.7% | 16.0% | 14.1% |
Very Difficult | 19.2% | 25.6% | 23.9% |
Cannot Generate | 20.2% | 43.9% | 44.2% |
In logistic regression analyses controlling for urban/rural location, practice size, practice ownership, teaching status, hospital affiliation, and practice type, the relationship between the presence of EHR and the ability to carry out each registry function remained robust. EHR adopters were more likely than non-adopters to be able to develop registries based on diagnosis (adjusted odds ratio [OR] 1.53, 95% confidence interval [CI] 1.25 - 1.86), laboratory results (OR 1.42, 95% CI, 1.22 - 1.66), and medications (OR 2.30, 95% CI, 1.96 - 2.70). Rural location, practice size, practice ownership, hospital affiliation, and practice type also remained significant correlates of one or more registry capability in the multivariate analyses (
Ability to perform registry functions according to practice characteristics (these data are weighted but not adjusted for confounding factors)
Percentage of physicians able to perform function | ||||
Diagnosis registry | Laboratory result registry | Medication registry | ||
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Rural | 78.9% | 58.9% | 62.6% | |
Urban | 79.9% | 55.9% | 55.3% | |
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≥ 6 physicians | 82.4% | 60.1% | 59.2% | |
3 - 5 physicians | 84.8% | 63.4% | 53.9% | |
1 - 2 physicians | 75.8% | 50.6% | 54.8% | |
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Full owner | 77.8% | 51.2% | 54.1% | |
Part owner | 81.6% | 49.9% | 48.3% | |
Non owner | 81.6% | 66.6% | 61.7% | |
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Involved in teaching | 85.0% | 63.2% | 61.8% | |
Not involved in teaching | 76.9% | 52.3% | 52.5% | |
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Hospital based practice | 81.9% | 69.9% | 65.2% | |
Non-hospital based practice | 79.4% | 54.5% | 54.8% | |
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Solo primary care practice | 74.2% | 57.2% | 61.7% | |
Solo specialty care practice | 77.1% | 47.0% | 55.8% | |
Primary care group/partnership | 88.6% | 71.4% | 67.2% | |
Single specialty group/partnership | 78.5% | 56.0% | 44.5% | |
Multi-specialty group/partnership | 84.5% | 58.7% | 59.7% | |
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Yes | 85.9% | 66.7% | 71.6% | |
No | 78.0% | 52.9% | 51.1% |
a
b
c
d
e
Multivariate correlates of registry function capability
Diagnosis registry |
Laboratory result registry |
Medication registry |
||
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Rural | 0.95 (0.73 - 1.23) | 1.08 (0.86 - 1.34) | 1.32 (1.05 - 1.65) | |
Urban | 1 (Ref) | 1 (Ref) | 1 (Ref) | |
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≥ 6 physicians | 1.09 (0.85 - 1.41) | 0.92 (0.74 - 1.14) | 1.10 (0.89 - 1.37) | |
3 - 5 physicians | 1.62 (1.29 - 2.03) | 1.39 (1.16 - 1.68) | 1.20 (1.00 - 1.44) | |
1 - 2 physicians | 1 (Ref) | 1 (Ref) | 1 (Ref) | |
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Full owner | 1.28 (1.04 - 1.58) | 0.71 (0.60 - 0.85) | 0.65 (0.54 - 0.78) | |
Part owner | 1.19 (0.92 - 1.53) | 0.53 (0.43 - 0.65) | 0.71 (0.58 - 0.87) | |
Non owner | 1 (Ref) | 1 (Ref) | 1 (Ref) | |
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Involved in teaching | 1.42 (1.19 - 1.70) | 0.98 (0.85 - 1.13) | 1.08 (0.94 - 1.25) | |
Not involved in teaching | 1 (Ref) | 1 (Ref) | 1 (Ref) | |
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Hospital based practice | 1.09 (0.85 - 1.39) | 1.87 (1.52 - 2.30) | 1.35 (1.10 - 1.66) | |
Non-hospital-based practice | 1 (Ref) | 1 (Ref) | 1 (Ref) | |
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Solo primary care practice | 0.67 (0.47 - 0.96) | 1.23 (0.92 - 1.65) | 1.97 (1.46 - 2.66) | |
Solo specialty care practice | 0.84 (0.60 - 1.17) | 0.90 (0.68 - 1.18) | 1.78 (1.35 - 2.34) | |
Primary care group/partnership | 1.47 (1.07 - 2.02) | 1.90 (1.50 - 2.42) | 1.61 (1.26 - 2.04) | |
Single specialty group/partnership | 0.70 (0.54 - 0.91) | 0.91 (0.74 - 1.13) | 0.62 (0.50 - 0.77) | |
Multi-specialty group/partnership | 1 (Ref) | 1 (Ref) | 1 (Ref) | |
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Yes | 1.53 (1.25 - 1.86) | 1.42 (1.22 - 1.66) | 2.30 (1.96 - 2.70) | |
No | 1 (Ref) | 1 (Ref) | 1 (Ref) |
OR = adjusted odds ratio; CI = confidence interval
Ref: Reference Category
We also observed a relationship between use of key EHR features and ability to perform related registry functions. Specifically, within the group of physicians who had access to an EHR in their practice, 90.4% of physicians who reported using an electronic problem list at least some of the time had the ability to perform diagnosis registry functions, while only 67.7% of physicians using an EHR without access to an electronic problem list could perform these functions (
While many studies have demonstrated the value of being able to perform registry functions for improving the quality and safety of health care [
Having EHRs was strongly associated with the reported ability to generate registries based on diagnosis, laboratory test result, or medication, but even among EHR users, 14% could not generate lists of diagnoses, 33% could not do so for laboratory tests, and 28% could not do so for medications. Furthermore, we found that physicians who reported active use of key EHR functions were considerably more likely to report being able to generate registries. Thus, these data suggest that EHRs appear important for delivering care using registries, and that most but not all EHR users could generate registries using their electronic records.
We are uncertain about why some physician practices with EHRs were unable to create registries. Many of these practices reported using EHRs which we knew to have this capability. It is likely that at least some of the EHR users who reported an inability to generate registries actually have the ability to generate them using their EHR, but are unaware of the feature. This suggests that improvements in documentation, training, and ease of use to help more physicians take advantage of the existing registry capabilities of their EHRs may be useful.
We were also a bit surprised by the relatively high proportion of EHR non-users who reported being able to generate registries. We are uncertain as to the mechanism employed by these users, since our survey did not ask them to explain how they were generating registries. These users may have been using retrospective chart review, prospective tracking, or analysis based on administrative data (such as billing and claims data in a practice management system). Each of these methods has a significant downside. Retrospective chart review is extremely time-consuming and error prone; prospective tracking requires criteria to be developed in advance; and non-clinical data are often less sensitive and specific than clinical data.
Taken together, our findings raise concerns about the ability of many ambulatory care practices, particularly the majority of practices without EHRs, to provide effective care for their patients on a population level. Physicians and practices need to consider population-level care management, not only as an essential component to effective practice within the Chronic Care Model [
EHRs can and should either include the inbuilt ability to query across patient records by a variety of criteria, or support extracting patient data which can be fed into other applications which do this. The ability to generate registries by diagnosis is common in many commercial EHR systems. In fact, it is a requirement of the 2007 and 2008 Certification Commission for Health Information Technology (CCHIT) criteria for ambulatory EHR certification [
It is also worth noting that the ability to create registries in an EHR is generally predicated on the use of structured documentation features within the EHR. For example, if a clinician documents patient problems only in unstructured clinical notes, it is nearly impossible in most commercially available EHRs to build medication registries based on this unstructured information. However, if the clinician uses a structured medication list with a controlled medication vocabulary, generating such a registry becomes much easier.
Finally, our survey was conducted in 2005. Since then, adoption of EHRs in ambulatory practices has increased somewhat [
Our findings have several important implications for physicians, for the health care system, and for developers of electronic health records. Because our findings suggest that the ability to generate registries is less than universal, and because generating registries is integral to quality and safety enhancing activities, it may be necessary to take steps to increase these capabilities in office practice. Providing physicians and practices with training and activities to increase awareness of the role of generating registries may be beneficial, but these changes are unlikely to be sufficient. Incentives also likely play an important role; physicians are more likely to adopt and use registry functions if financial incentives are in place to do so [
The study has several limitations. First, our survey was limited to physicians in ambulatory care in Massachusetts, and the results may not be generalizable to other states or regions. However, given that Massachusetts is a state in which more than 45% of physicians have EHRs [
Another limitation is the self-reported nature of survey studies such as ours. We are, of course, not truly measuring physicians’ abilities to generate registries, but instead their self-reports of the ability to generate three specific types of registries. This raises the possibility of social desirability bias influencing physicians’ responses to survey questions. However, if this bias were present, then one might expect that physicians overestimated their abilities to perform registry functions, which would mean that even fewer physicians than reported have the ability to generate registries. Also, our survey asked providers how easily they could perform registry functions but did not ask how frequently they actually did perform such functions, or for what purposes and with what results. It is important to note that, among those practices that reported the ability to make these registries, we do not know the frequency with which they did so. It is possible that some practices, although able to create the registries, never actually do. Future qualitative and quantitative studies should explore how physicians and practices are using registries, as well as the barriers to, and facilitators of, effective use of these important tools. Intervention studies will then be able to test strategies for improving physicians’ use of registries to improve quality of care and patient safety.
Finally, our survey was limited to registries of diagnoses, medications and lab results. Other types of registries exist, such as registries of patients receiving a particular surgical procedure, which are often used for tracking quality and outcomes, tumor registries, and registries of implanted devices, such as implantable cardiac defibrillators or pacemakers, which are important in the event of a recall. Such registries are generally used in specific specialties, and it would be worthwhile to survey specialists about their use of these special-purpose registries.
While registry functions are available to many physicians, their availability is far from universal. Because generating registries is essential for population health management activities associated with improved quality, safety, and efficiency, it is important that their availability increase. Adoption of EHRs appears to be a useful step toward this end, since practices with EHRs are significantly more likely to be able to carry out registry functions. CCHIT should intensify and expand its requirements for registry function capabilities, and commercial EHR products without these capabilities should be extended to provide them. Health policy makers and health care leaders can then develop and disseminate strategies for using registries for improving patient safety and the quality of health care.
This study was funded in part by the United States Agency for Healthcare Research and Quality cooperative agreement #1UC1HS015397-01 and the Massachusetts e-Health Collaborative. The Agency for Healthcare Research and Quality and the Massachusetts e-Health Collaborative had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality or the Massachusetts e-Health Collaborative.
None declared.
Massachusetts Survey of Physicians and Computer Technology
Certification Commission for Health Information Technology
electronic health record
institutional review board