Does Improved Access to Care Affect Utilization and Costs for Patients With Chronic Conditions?

Published Online: October 01, 2004
Leif I. Solberg, MD; Michael V. Maciosek, PhD; JoAnn M. Sperl-Hillen, MD; A. Lauren Crain, PhD; Karen I. Engebretson, BA; Brent R. Asplin, MD, MPH; and Patrick J. OfConnor, MD, MPH

Objective: To determine whether a major improvement in access (ie, implementing an open access system) in a large multispecialty medical group during 2000 was associated with changes in utilization or costs for patients with diabetes, coronary heart disease (CHD), or depression.

Study Design: Multilevel regression analysis of health plan administrative data.

Patients and Methods: Approximately 7000 patients with diabetes, 3800 with CHD, and 6000 with depression who received all of their care in this care system served as the subjects for this study. Utilization and costs between 1999 and 2001 (before and after implementation of open access) were compared for these patients. The main outcome measures were rates of inpatient admissions and various types of outpatient encounters as well as associated costs for these subjects.

Results: Between 1999 and 2001, total office visit changes were small and varied with condition, but the proportion of these visits made to primary care physicians increased significantly by an absolute 5% to 9% and primary care physician continuity increased for each condition. Urgent care visits also decreased significantly by an absolute 5% to 9%, but there was no change in emergency department visits or hospital admissions. Total costs of care for these patients were much larger than those for the overall population of the medical group, but increased at a similar rate.

Conclusion: A major improvement in patient access to primary care clinics was associated with increased use and continuity of primary care for patients with 3 chronic conditions, but did not affect overall resource use.

(Am J Manag Care. 2004;10:717-722)

The Institute of Medicine's 2001 report Crossing the Quality Chasm highlighted the chasm between "the care we have and the care we could have."1 Serious deficits in quality of healthcare have been further documented by McGlynn et al's study of national adherence to 439 indicators for 30 conditions.2 The chasm report emphasized the particular need to improve care for patients with chronic conditions and was followed by a 2003 report identifying the 20 priority areas for transforming care.3 Many of these 20 were common chronic conditions for which improving quality necessarily involves addressing the 6 aims or dimensions of quality identified by the chasm report: safety, timeliness, effectiveness, efficiency, equity, and patient-centeredness.

Each of these dimensions now is receiving increased attention, but it seems that timeliness ("reducing waits and sometimes harmful delays") is actually being improved, at least in terms of access to primary care. Murray and Tantau have been major innovators with respect to access, helping many medical groups to make substantial improvements in access through an approach called Advanced Access or Second Generation Open Access.4-6 In this approach, the goal is to be able to offer any patient a visit the same day that he or she calls, with the patient's personal physician if that physician is in the office that day.

In theory, a medical practice that can offer this type of access might expect to see a decrease in unnecessary office visits, cancellations, and no-shows; decreased urgent-care and emergency department (ED) visits; decreased hospitalizations because serious illnesses are caught at an earlier stage; greater continuity of care; and perhaps a decrease in total office visits.4-7 If these changes occur, it seems likely that another of the 6 dimensions, efficiency, might be improved as well, with decreased costs for both the care system and for patients. Whether and to what extent these effects actually occur is unknown, however, because no published studies thoroughly document such changes.

Because so much of the attention to the need for quality improvement has focused on patients with chronic conditions, another open question concerns the effect of access improvement on these frequent and high-cost users of the care delivery system. Murray and Berwick suggest that such patients may fare better with prescheduled visits rather than expecting them to simply call for an appointment on the day that their routine follow-up is needed.4 Others have been concerned that patients with chronic disease may fall through the cracks of a care system that becomes increasingly oriented toward acute and same-day care.

Because our large multispecialty medical group recently greatly improved primary care access using the Advanced Access model of Murray and Tantau,4-6 we conducted this study to assess the impact of increased access on utilization and cost of care. Over the course of 1 year (2000), primary care access for our patients, measured by third-next-available appointment, improved from an average of 17.8 days in 1999 to 4.2 days in 2001. Murray notes that this is a better measure of real access than the first- or second-next-available appointment because those appointments are more likely to represent random cancellations.4 The range of third-next-available appointments among 17 primary care clinics in 2001 varied from 1.7 to 6.2 days.

Because we were particularly concerned with the effects on patients with chronic conditions (diabetes, coronary heart disease [CHD], or depression), we focused on those patients to learn whether the overall change in primary care access between 1999 and 2001 was associated with any significant changes in:

  • Visits to ambulatory care, primary care, ED, or urgent-care clinic.
  • Proportion of all visits that were in primary care and were for the patient's chronic condition.
  • Continuity of care with the same physician.
  • Hospital admissions and length of stay.
  • Total costs of care, including both inpatient and outpatient care.


This study was conducted in a 500-physician multi-specialty medical group that is owned by a health plan with 650 000 members. About 240 000 of these members are cared for by the medical group, most in the 17 primary care clinics included in this study. The other 410 000 members receive their care through about 50 medical groups in the region that contract separately with the health plan, and they are not part of this study.

In late 1999, the medical group leadership decided to undertake a major change in the approach to access, hoping to improve patient satisfaction as well as overall efficiency and, possibly, clinician job satisfaction.8 Therefore, the leadership engaged outside consultants to help conduct a series of full-day sessions during 2000 for representatives from all of its clinics and provided considerable training and consultative resources along with a deadline (January 1, 2001) to achieve full advanced access. This required marked standardization of schedule slots and extra visit time for clinicians to work down the backlog of their appointments, but there was no increase in care personnel or resources during this change. Several other major changes took place during this time period: the appointment-making process was centralized, physician compensation was gradually switched from salary to productivity, and major work flow redesign and cost restructuring were conducted to streamline support processes and reduce overhead.

Adult (age >18 years) patients with either diabetes, CHD, or depression were identified from health plan administrative databases by using algorithms that were modified from a previously described approach and validated against chart audits.9 For CHD or depression, these algorithms specified that patients have at least 1 inpatient diagnosis or 2 outpatient diagnoses in a given year with specified International Classification of Diseases, Ninth Revision codes (see Table 1). For diabetes, a patient could have filled a diabetes-specific medication or have had 1 inpatient or 2 outpatient diagnoses. These algorithms have estimated positive predictive values of .96 for diabetes, .95 for CHD, and .90-.95 for depression.


After identifying patients with each condition in each year from 1998 through 2001 who were enrolled for at least 11 months of that year, their utilization and cost data were collected from health plan administrative databases. Continuity of care was calculated based on the "continuity of care" method for the distribution of visits by a patient among different providers in each year.10 The formula is ∑(visiti 2) − ∑(visiti)/[∑(visiti)×(∑visiti) − 1)] (where i = number of visits to a provider). Continuity of care tends to increase as the total number of visits increase, but is unaffected by the sequencing of visits.

Multilevel linear and nonlinear (ie, logistic) regression models were used to compare utilization in 1999 versus 2001 (before and after the change in access) with MLwiN software version 1.10 (Multilevel Models Project, London, UK). The linear models specified a normally distributed dependent variable and used the Iterative Generalised Least Squares estimation method. The nonlinear models specified a binomially or extra-binomially distributed dependent variable (as appropriate) and a logit link function, and used the penalized quasi-likelihood estimation method with first-order linearization. For each dependent variable, an intercept-only model identified the significant random-variance components to be included in the predictive model. A 3-level (time within patient within provider) random-variance structure was attempted for all variables, although the provider level was omitted if not significant. Up to 2 observations per person (eg, continuity of care measured in 1999 and in 2001) were included in each model. A dummy variable for year (reference = 1999) indicated whether the values for the dependent variable were different by year, and it was the parameter of interest in all models. Sex, age in 1998, and a year-specific Charlson score greater than or equal to 3 (as a measure of disease severity and comorbidities) were included as covariates.11,12

"Costs" were measured as paid amounts from health plan administrative data. For contracted care providers, paid amounts are those actually paid by the health plan. For providers within the staff-model medical group (studied here), the paid amounts represent approximately what the health plan would have paid to a contracted provider. Costs were adjusted to year 2000 dollars by using the medical-care component of the consumer price index for all urban consumers. All steps in the development of the identification system, aggregation of data, and data analysis were approved in advance and monitored by the local institutional review board. Because aggregate de-identified claims data were used in the analysis, the institutional review board did not require informed consent.


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