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. Author manuscript; available in PMC: 2024 May 1.
Published in final edited form as: Arch Phys Med Rehabil. 2023 Jan 31;104(5):719–727. doi: 10.1016/j.apmr.2022.11.018

Prevalence and predictors of ambulatory care physicians’ documentation of mobility limitations in older adults

Valerie Shuman a, Jennifer S Brach a, Jonathan F Bean b,c,d, Janet K Freburger a
PMCID: PMC10164109  NIHMSID: NIHMS1879287  PMID: 36731767

Abstract

Objective:

To determine how often physicians document mobility limitations in visits with older adults, and which patient, physician, and practice characteristics associate with documented mobility limitations.

Design:

We completed a cross-sectional analysis of National Ambulatory Medical Care Surveys, years 2012–2016. Multivariate analyses were conducted to identify patient, physician, and practice-level factors associated with mobility limitation documentation.

Setting:

Ambulatory care visits.

Participants:

We analyzed visits with adults 65 years and older. Final sample size represented 1.3 billion weighted visits.

Intervention:

N/A

Main Outcome Measure:

We defined the presence/absence of a mobility limitation by whether any ICD-9 or ICD-10 code related to mobility limitations were documented in the visits.

Results:

The overall prevalence of mobility limitation documentation was 2.4%. The most common codes were falls-related. Patient-level factors more likely to be associated with mobility limitation documentation were visits by individuals over 85 years of age, relative to 65–69 years, (OR 2.32, 95% CI 1.76–3.07]; with a comorbid diagnosis of arthritis (OR 1.35, 1.18–2.01); and with a comorbid diagnosis of cerebrovascular disease (OR 1.60, 1.13–2.26). Patient-level factors less likely to be associated with mobility limitation documentation were visits by males (OR 0.80, 0.64–0.99); individuals with a cancer diagnosis (OR 0.76, 0.58–0.99); and by individuals seeking care for a chronic problem (relative to a new problem [OR 0.36, 0.29–0.44]). Physician-level factors associated with an increased likelihood of mobility limitation documentation were visits to neurologists (ORs 4.48, 2.41–8.32) and orthopedists (OR 2.67, 1.49–4.79) compared to primary care physicians. At the practice-level, mobility documentation varied based on the percentage of practice revenue from Medicare.

Conclusions:

Mobility limitations are under-documented and may be primarily captured when changes in function are overt.

Keywords: Mobility Limitation, Aged, Physicians, Primary Care, Documentation

The 4Ms Framework identifies ‘what Matters most’, Medication, Mentation, and Mobility as the 4 essential elements of age-friendly care for older adults.1,2 Maintenance of physical function and mobility “matters” for many older adults.3,4 Mobility is also a centerpiece of physical independence. Mobility limitations in older adults are related to serious health and social consequences. Defined as self-reported difficulty walking several blocks or climbing a flight of stairs5, mobility limitations are strong predictors of falls, major disability, nursing home placement, and early mortality.6–9 Approximately 30–40% of older adults in the United States report mobility limitations with direct and indirect costs estimated at $42 billion annually.6,10–13

Early identification and treatment of mobility limitations in older adults help prevent catastrophic downstream consequences, such as injurious falls, hospitalizations, and dependence in activities of daily living.14,15 Effective interventions for addressing the physiologic changes underlying the incremental onset of mobility limitations include rehabilitation (physical therapy or occupational therapy), community-based exercise programs, and/or self-management programs.16–22 These interventions can be effective in improving mobility, preventing further decline in mobility, or slowing the decline in mobility.

To address ‘what matters most’ to older adults, healthcare providers are encouraged to screen for mobility limitations and refer at-risk older adults to appropriate treatment.14,15,23 Physicians, particularly primary care physicians, are well-positioned to complete mobility screenings in older adults.23–25 Documentation of patients’ mobility limitations is a key step to accessing appropriate treatment for preventing or slowing the progression of such limitations.26 Furthermore, understanding the patient and practice characteristics associated with documentation of mobility limitations may provide guidance on increasing this documentation as more healthcare systems adopt age-friendly care.27 Data suggest patients largely receive the recommended assessments and interventions for mobility limitations when physicians document risk factors such as gait and balance deficits.26

Despite the high prevalence of self-reported mobility limitations in older adults, the negative consequences of immobility, and presence of effective evidence-based treatments to promote mobility, little is known about the extent to which physicians identify and document mobility limitations in older adults. We aimed to determine the extent to which ambulatory care physicians document mobility limitations in older adults and the patient-, physician- and practice-level characteristics associated with this documentation.

METHODS

Data source

We examined 5 years of data (2012–2016) from the National Ambulatory Care Medical Survey (NAMCS), an annual national probability sample survey of ambulatory care visits to nonfederal office-based physicians.28,29 The NAMCS utilizes a stratified two-stage sample selection approach of first selecting physicians and then selecting visits within physician. Further details on the methodology are available elsewhere.28 The NAMCS captures de-identified physician documentation of patient encounters. Data collected include information on the patient visit (e.g., patient demographics, patient concerns, physician diagnoses). Data on physician and practice characteristics are also included. The University of Pittsburgh Institutional Review Board classified this study as exempt from review as the data are publicly available.

Study variables

We limited our analysis to visits with individuals 65 years and older. Our outcome of interest was documentation of any mobility limitation (yes/no) during the visit based on physician diagnosis codes, injury codes, or the patient’s “reasons for visit”.

For physician diagnosis codes, we identified several International Classification of Diseases (ICD) −9 and −10 codes indicative of mobility limitations or falls (sample years 2012–2015 used ICD-9 codes, and 2016 used ICD-10 codes).30,31 While there is an ICD code specific for ‘impaired mobility’ (V49.89 and Z74.09, in ICD-9 and −10, respectively), we chose to broadly identify mobility limitations through multiple codes. This choice was made given the limitations of administrative coding32 and because few visits in the data used the impaired mobility diagnosis code. We examined all diagnoses associated with the visit. The specific codes we used captured diagnoses related to walking (unattributable to specific neurologic conditions, such as cerebellar ataxia) and lower extremity weakness (Supplementary Table S1).33,34 We included injury codes, as abstracted from the survey text by the National Center for Health Statistics, related to ground-level falls as indicators of balance impairments or walking problems.29

Patients’ “reasons for visits” are categorized based on a classification system developed by The American Medical Records Association under the National Center for Health Statistics.35 These are distinguished from “physician diagnoses” as they represent the patient’s perceived need for seeking medical care, as expressed by the patient. Reasons are sorted into one of 8 modules (e.g., symptom module, test results module) and then further specified.36 We assessed “reasons for visit” related to lower extremity muscle weakness, falls, and disorders of motor functions (which include items such as difficulty in walking or unsteady gait).

We hypothesized several patient-, physician-, and practice-level characteristics would be associated with documentation of a mobility limitation, based on the literature and clinical experience. For example, patient characteristics such as older age or a diagnosis of arthritis may increase the likelihood of documenting mobility limitations. Likewise, physicians who treat more patients with mobility limitations (e.g., neurologists, orthopedists) may be more likely to document mobility limitations. And practice characteristics that may influence workflow and processes of care may have an impact on physicians’ documentation practices. Patient demographic characteristics included age, sex, race and ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, or non-Hispanic Other) and primary insurance (Medicare, Medicaid, private insurance, or other). To maximize our sample size for analyses, we utilized imputed values for race and ethnicity (25.6% imputed).29 Patient clinical characteristics included number of chronic conditions, presence of specific health conditions (e.g., arthritis, depression), and major reason for visit (new problem, chronic problem, pre- or post- surgical, or preventive care). Physician characteristics included specialty [primary care (inclusive of family medicine practitioners, geriatricians, and general internists), neurology, orthopedics, cardiovascular, or other], physician type (Doctor of Medicine or Doctor of Osteopathy), and whether the physician was the patient’s primary physician. Physician process characteristics included minutes spent with the patient, whether an advanced practice provider (physician assistant, nurse practitioner) was seen, the types of special examinations completed (e.g., neurologic, foot), and services or tests ordered (e.g., physical therapy referral or a bone mineral density test). Practice characteristics included practice region (Northeast, Midwest, South, or West census region), practice ownership (physician or physician group, academic health center, or insurance company/health maintenance organization), practice type (solo or group), and percent of practice revenue from Medicare (traditional fee-for-service or Medicare Advantage).

Data analysis

We conducted all analyses using Stata 16.1 (StataCorp. 2019) survey commands, which weights the visits and accounts for the multistage survey design. We generated descriptive statistics on patient, clinical, and practice characteristics stratified by the presence/absence of mobility limitation-related documentation. We then estimated multivariable logistic regression models with mobility limitation documentation (yes/no) as the dependent variable and patient, physician, and practice characteristics as the explanatory variables. To maximize our sample size, we created dummy variables for the measures missing data (Table 1). We assessed for multicollinearity of predictor variables using variance inflation factors. We conducted analyses on the entire sample and for the following subgroups: visits to primary care physicians and visits to specialist physicians. Percent of practice revenue from Medicare was missing for 14.2% of the visits. To determine the impact of using a dummy variable for the missing data, we conducted a sensitivity analysis excluding records with missing data.

RESULTS

Our sample consisted of 64,892 visits by patients 65 years of age and older, approximating 1.32 billion weighted visits (95% confidence interval [CI], 1.27 billion – 1.38 billion). Two percent of the visits had mobility limitation-related documentation (Table 1). The most common mobility limitation codes were related to falls (51.1%), with gait limitations (13.4%), strength deficits (14.6%), and other (20.9%) related codes accounting for the remainder (Supplementary Table S2). The greatest proportion of visits with mobility limitation-related documentation were from patient’s reasons for visit (50.6%), followed by injury codes (28.8%), and administrative ICD codes (20.6%). Visits to primary care physicians (PCPs) accounted for approximately 40% of our sample.

Table 1.

Patient demographic and clinical characteristics for visits in which mobility limitation documentation was present or absent

No mobility limitation documentation present (N=1,290,836a) 97.6% Mobility limitation documentation present (N=31,196a) 2.4% Total (N=1,322,033a)
Sociodemographic characteristics
Age, y, mean (SE) 75.0 (0.1) 77.1 (0.6) 75.0 (0.1)
Sex, % (SE)
 Female 56.4 (0.4) 65.6 (2.6) 56.6 (0.4)
 Male 43.6 (0.4) 34.4 (2.6) 43.4 (0.4)
Race/ethnicity, % (SE)
 Non-Hispanic White 77.9 (1.1) 82.4 (2.5) 78 (1.1)
 Non-Hispanic Black 8 (0.4) 6.9 (2.2)b 7.9 (0.4)
 Hispanic 9 (0.6) 7.2 (1.9) 8.9 (0.6)
 Non-Hispanic Other 5.1 (0.9) 3.5 (0.8) 5.1 (0.9)
Patient insurance, % (SE)
 Medicare 77 (0.6) 76.8 (2.6) 77 (0.6)
 Private Insurance 14.8 (0.5) 13.0 (1.7) 14.8 (0.5)
 Medicaid 2 (0.2) 1.0 (0.4)b 2 (0.2)
 Other Payer 2.1 (0.2) 2.1 (0.7)b 2.1 (0.2)
 Missing 4 (0.3) 7.1 (2.0) 4.1 (0.3)
Clinical characteristics
Number of comorbid conditions, % (SE)
 No chronic conditions 15.4 (0.4) 13.9 (1.7) 15.4 (0.4)
 1–2 condition 44 (0.6) 38.4 (2.8) 43.9 (0.6)
 3–4 conditions 29.4 (0.5) 32.4 (2.2) 29.5 (0.5)
 5–6 conditions 8 (0.4) 9.0 (1.3) 8 (0.4)
 More than 6 conditions 1.4 (0.2) 4.2 (2.2) 1.5 (0.2)
 Missing 1.7 (0.2) 2.0 (0.7)ǂ 1.7 (0.2)
Specific clinical conditions, % (SE)
 Arthritis 23.6 (0.7) 41.3 (3.6) 23.9 (0.8)
 Cancer 14.2 (0.5) 8.7 (1.0) 14.1 (0.5)
 Cerebrovascular disease 4.5 (0.2) 10.6 (2.2) 4.6 (0.2)
 Chronic obstructive pulmonary disorder 7.6 (0.3) 9.0 (2.2) 7.6 (0.3)
 Congestive heart failure 4.4 (0.2) 3.6 (0.7) 4.4 (0.2)
 Depression 8.9 (0.3) 13.3 (1.6) 9 (0.3)
 Obesity 6.9 (0.3) 6.8 (1.6) 6.9 (0.3)
 Osteoporosis 6.6 (0.3) 8.2 (1.3) 6.6 (0.3)
Reason for visit, % (SE)
 New problem 23.8 (0.5) 46.0 (3.2) 24.3 (0.5)
 Chronic problem 51.7 (0.7) 36.6 (3.0) 51.3 (0.7)
 Pre- or post-surgical 13.5 (0.4) 6.6 (0.9) 13.4 (0.4)
 Preventive care 8.8 (0.5) 7.6 (4.4)b 8.8 (0.5)
 Missing 2.2 (0.2) 3.2 (1.1)b 2.2 (0.2)
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a

All weighted N’s are reported in thousands.

b

Standard error is > 30%.

Table 1 presents descriptive data on patient characteristics of the ambulatory care visits, stratified by the presence or absence of a mobility limitation documentation. Visits by older individuals were more likely to have a mobility limitation documented. A greater proportion of visits by females; individuals with more comorbid conditions; individuals with arthritis, cerebrovascular disease, or depression; and individuals visiting the physician for a new problem included mobility limitation-related documentation. Visits by those with a cancer diagnosis and for a chronic problem were less likely to have mobility limitation-related documentation present. Missing data on patient insurance, comorbid conditions, and reason for visit were less than 5 percent.

Descriptive data on physician and practice characteristics, stratified by the presence of mobility limitation documentation, are presented in Table 2. A greater proportion of visits including a neurological examination and visits with an orthopedist or neurologist included mobility limitation-related documentation. Visits including interventions such as injury prevention counseling, ordering durable medical equipment (e.g., walkers or canes), and physical therapy were also more likely to include mobility limitation-related documentation. Missing data on physician and practice characteristics was less than 5 percent, excepting Medicare revenue data.

Table 2.

Physician and practice characteristics for visits in which mobility limitation documentation was present or absent

No mobility limitation documentation present (N=1,290,836a) 97.6% Mobility limitation documentation present (N=31,196a) 2.4% Total (N=1,322,033a)
Physician process characteristics
Time spent with physician, minutes (SE) 22.3 (0.2) 22.5 (0.6) 22.3 (0.2)
Advanced practitioner seen, % (SE) 7.1 (0.6) 6.9 (1.4) 7.1 (0.6)
Neurologic examination completed, % (SE) 11.2 (0.9) 25.5 (4.2) 11.6 (1)
Foot examination completed, % (SE) 4.2 (0.4) 7.4 (1.4) 4.3 (0.4)
Injury prevention counseling provided, % (SE) 2.3 (0.4) 7.6 (2.3)b 2.4 (0.4)
Exercise counseling provided, % (SE) 7.6 (0.6) 8.3 (2.0) 7.6 (0.6)
Bone mineral density scan ordered, % (SE) 1.1 (0.1) 3.4 (2.3)b 1.1 (0.1)
Physical therapy ordered, % (SE) 1.6 (0.1) 11.3 (1.6) 1.8 (0.1)
Durable medical equipment ordered, % (SE) 0.7 (0.1) 3.7 (0.9) 0.8 (0.1)
Home health care ordered, % (SE) 0.5 (0.2)b 3.5 (2.2)b 0.6 (0.2)b
Physician characteristics
Physician specialty, % (SE)
 Primary Care 37.8 (1.1) 44.6 (3.7) 37.9 (1.2)
 Neurology 1.5 (0.2) 10.5 (1.7) 1.7 (0.2)
 Orthopedics 4.9 (0.3) 21.6 (2.3) 5.3 (0.4)
 Cardiovascular 7.9 (0.6) 3.6 (0.9) 7.8 (0.6)
 Other 47.9 (1.2) 19.7 (2.2) 47.3 (1.2)
Doctor of Medicine, % (SE) 94.3 (0.5) 89.5 (2.1) 94.2 (0.5)
Doctor of Osteopathy, % (SE) 5.7 (0.5) 10.5 (2.1) 5.8 (0.5)
Patient’s primary care provider (PCP), % (SE)
 Yes 37.3 (1.1) 39.7 (3.7) 37.4 (1.1)
 No 59.3 (1.1) 58.1 (3.7) 59.3 (1.1)
 PCP status missing 3.4 (0.2) 2.2 (0.5) 3.3 (0.2)
Practice characteristics
Census region, % (SE)
 Northeast 20.1 (0.7) 20.0 (2.4) 20.1 (0.7)
 Midwest 19.2 (0.6) 25.0 (2.5) 19.3 (0.6)
 South 37 (1) 30.2 (2.8) 36.9 (1)
 West 23.7 (1.2) 24.8 (4.0) 23.7 (1.2)
Ownership, % (SE)
 Physician or Physician Group 78.7 (0.9) 74.3 (2.7) 78.6 (0.9)
 Medical/Academic Health Center 8.2 (0.6) 8.5 (1.5) 8.2 (0.6)
 Insurance company, health plan, or HMO 10.2 (0.6) 13.7 (2.1) 10.3 (0.7)
 Ownership Missing 2.9 (0.3) 3.6 (0.9) 2.9 (0.3)
Practice type, % (SE)
 Solo practice 35.4 (1.3) 30.0 (3.0) 35.3 (1.3)
 Group practice 64.6 (1.3) 70.0 (3.0) 64.7 (1.3)
Medicare revenue, % (SE)
 0 to 25% 20.2 (1) 30.6 (4.2) 20.4 (1.1)
 26 to 50% 39.4 (1.3) 34.7 (2.9) 39.3 (1.3)
 Greater than 50% 25.9 (1) 19.5 (2.3) 25.7 (1)
 Medicare Missing 14.6 (0.8) 15.2 (2.1) 14.6 (0.8)
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a

All weighted N’s are reported in thousands.

b

Standard error is > 30%.

Several patient characteristics were associated with the outcome in multivariate analyses (Figure 1). Visits by patients older than 85 years were more than twice as likely as those 65–69 to include mobility limitation-related documentation. Other characteristics increasing the likelihood of mobility limitation-related documentation included a diagnosis of arthritis or cerebrovascular disease. Characteristics decreasing the likelihood of a documented mobility limitation include visits by males, those with a cancer diagnosis, and visits for anything other than a new problem (i.e., chronic, surgical, or preventive care visits). Physician process characteristics positively associated with mobility limitation-related documentation included completion of a neurologic examination, injury prevention counseling, and orders for physical therapy, home health care, and durable medical equipment (Figure 2).

Figure 1.

Figure 1.

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Association between patient sociodemographic and health characteristics of visits and mobility limitation documentation.

Forest plot of association point estimates between visit patient characteristics and presence of mobility limitation documentation. Estimates are controlled for reason for visit, time spent with physician, whether an advanced practitioner was seen, completion of interventions (i.e., neurologic examination, foot examination, injury prevention counseling, exercise counseling) or orders (i.e., physical therapy, durable medical equipment, home health care), physician specialty, physician type, primary care status, practice geographic region, practice ownership and type, and Medicare-based revenue.

Figure 2.

Figure 2.

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Association between physician process characteristics of visits and mobility limitation documentation.

Forest plot of association point estimates between physician process characteristics of visits and presence of mobility limitation documentation. Estimates are controlled for patient age, sex, race and ethnicity, primary patient insurance, comorbid burden, and specific clinical conditions (i.e., arthritis, cancer, cerebrovascular disease, chronic obstructive pulmonary disorder, congestive heart failure, depression, obesity, and osteoporosis), physician specialty, physician type, primary care status, practice geographic region, practice ownership and type, and Medicare-based revenue.

Multiple physician characteristics were also associated with mobility limitation-related documentation (Figure 3). Compared to primary care physicians, visits with neurologists and orthopedists were associated with increased likelihoods of mobility limitation documentation. Visits with an osteopathic physician increased odds of mobility limitation-related documentation relative to visits with allopathic physicians. Alternatively, visits with cardiologists and other physicians (e.g., endocrinologists, gastroenterologists, etc.) were associated with lowered odds of a mobility limitation compared to those with primary care physicians. Few practice characteristics were associated with mobility limitation-related documentation, except for visits to practices receiving 25–50% of their revenue from Medicare (relative to receiving 0–24% Medicare revenue) were less likely to have mobility limitation documentation.

Figure 3.

Figure 3.

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Association between physician and practice characteristics of visits and mobility limitation documentation.

Forest plot of association point estimates between visit physician and practice characteristics and presence of mobility limitation documentation. Estimates are controlled for patient age, sex, race and ethnicity, primary patient insurance, comorbid burden, and specific clinical conditions (i.e., arthritis, cancer, cerebrovascular disease, chronic obstructive pulmonary disorder, congestive heart failure, depression, obesity, and osteoporosis), reason for visit, time spent with physician, whether an advanced practitioner was seen, and completion of interventions (i.e., neurologic examination, foot examination, injury prevention counseling, exercise counseling) or orders (i.e., physical therapy, durable medical equipment, home health care).

Subgroup analyses

When we limited our sample to visits to primary care providers only, our results were similar to the full sample analysis, though effect sizes for significant variables were sometimes larger (both for positive and negative associations) (Supplementary Table S3). One notable difference was visits by individuals in the ‘other’ race/ethnicity category were less likely to be associated with mobility limitation documentation relative to visits by non-Hispanic Whites, whereas race/ethnicity were unassociated with mobility documentation in the full model.

Of visits to specialists, 2.11% had mobility limitation-related documentation. Like the primary care physician subgroup analysis, many predictors significantly associated with mobility limitation-related documentation were the same as in the full model (Supplementary Table S4). Factors unassociated in the full model, but significantly associated with an increased likelihood of mobility limitation-related documentation in the specialist subgroup analysis included the presence of a depression diagnosis, completion of a foot examination, and more than 10 minutes spent with the physician. Presence of congestive heart failure and patient insurance other than Medicare (i.e., Medicaid or private payer) lowered the odds of mobility limitation-related documentation being present in the visit in this subgroup.

Visits missing percent of practice revenue from Medicare accounted for 14.2% of the records. Most significant associations were not meaningfully different from the full model (Supplementary Table S5). Visits where a bone mineral density test were ordered had increased likelihood of mobility limitation-related documentation being present, whereas visits with Medicaid as the patient’s primary insurer had lowered likelihoods of mobility documentation being present.

DISCUSSION

Age-friendly care for older adults requires addressing mobility limitations early to maximize physical independence and decrease the risk of adverse outcomes and healthcare costs associated with immobility.5,37,38 We aimed to determine the extent to which ambulatory care physicians document mobility limitations in older adults and to identify the patient-, physician-, and practice-related factors associated with the documentation. Our findings suggest mobility limitations in older adults are not routinely documented during ambulatory care visits. Our sample prevalence of any mobility limitation documentation (2.36%) was much lower than prevalence estimates of mobility limitation self-reported by community-dwelling adults 65 years and over, which range from 24% to 47%.10–13 Under-documentation indicates a gap between physician documentation and ‘what matters most’ to older adults.1,2 Furthermore, it may lead to lack of access to appropriate care for a condition with serious consequences.6,7,9,37,39,40 If physicians are not identifying mobility limitations in their older patients, these patients may be missing opportunities for effective interventions.14,17,41

Our results suggest physicians likely document mobility limitations and associated diseases or conditions when they overtly impact patients’ function or quality of life. History of arthritis or cerebrovascular disease were positively associated with mobility limitation documentation. The positive association of arthritis with documentation is notable because the diagnosis of arthritis does not itself indicate mobility limitations; many individuals experience mild to moderate arthritis with aging. Previous literature also suggests that patients underreport arthritis and other diseases that may affect mobility unless the disease is overtly impacting daily function.42–44 While history of cerebrovascular disease may be a more likely indicator of mobility limitations (e.g., due to stroke) people with this diagnosis may also not have mobility limitations. The positive association we saw is likely indicative of cerebrovascular accidents being one of the more common diseases associated with associated with a documented mobility limitation

The presence of a cancer diagnosis significantly reduced the likelihood of mobility limitation-related documentation. This may be because patients being seen in primary care with a cancer diagnosis may not be experiencing mobility limitations, depending on the type of cancer. However, data suggest patients with a cancer diagnosis often experience mobility challenges.45 Visits may focus on medical complications, outweighing discussion of functional limitations.

Visits for a new problem increased the odds of a mobility limitation documentation relative to visits addressing chronic, surgical, or preventive care. Patients may bring issues related to mobility to the attention of providers when functional limitations newly outweigh other medical concerns.

Injury prevention counseling, a physical therapy referral, or a home health referral all were associated with increased odds of mobility limitation documentation. This makes theoretical sense, as these interventions address mobility limitations. Injury prevention counseling denotes clinically identifiable risk for future injury, such as unsteadiness during movement. Physical therapy referrals are often made for new onset concerns, such as falls or reports of impairments with functional consequences (e.g., pain that limits walking). A home health referral is necessary when medical or rehabilitative care is required, but the patient’s limitations (often functional) preclude easily leaving the home. Positive associations with these interventions are plausibly in response to discussion of mobility limitations during the visit.

Visits to a neurologist or orthopedist, relative to a PCP, also were associated with higher odds of mobility limitation documentation. Neurologists and orthopedists assess dimensions of mobility as part of their specialization; neurologists assess neuromotor function and orthopedists assess musculoskeletal aspects of mobility. Alternatively, visits with cardiologists had lower odds of mobility limitations than those with PCPs. While individuals with cardiovascular concerns are more likely to experience mobility limitations than those who do not46, cardiologists primarily assess physiologic issues, not functional ones.

Odds of mobility limitation-related documentation were lower for visits in practices receiving between 25–50% of their revenue from Medicare. Practices receiving a high percentage of revenue from Medicare see many older adults, the population likeliest to have mobility limitations. One potential explanation for this difference is clinics heavily reliant on Medicare reimbursement require shorter appointment times or fewer clinicians to operate to make up for the lower revenue47, increasing competing demands during visits.

Increasing physician office use of simple assessment tools may increase documentation of a highly prevalent condition. Multiple self-report and performance-based measures are clinically viable and powerful assessments.5,38,48 Measuring gait speed is an additional no-cost, low burden, and safe test that should become part of routine clinical assessments of older adults.15,40,49,50 This assessment could be carried out by support staff in the physician’s practice.

In a national survey, over three-quarters of participating primary care physicians reported routine discussion of mobility concerns with their older adult patients.51 Documentation may not reflect reality and next steps may include determining physician perception of the importance of documenting mobility limitations.27 Accurate documentation improves follow-up and treatment for mobility limitations.52 If only overt cases of mobility limitations are documented, individuals at risk for decline but not yet experiencing mobility disability (i.e., the inability to ambulate without great difficulty or assistance)53 may not receive the appropriate treatment. Documentation of mobility limitations increases opportunity for successful intervention and better aligns care with patient priorities.

Limitations

This study is a novel investigation of prevalence of, and factors associated with, mobility limitation documentation among ambulatory care visits, but it is not without limitations. The NAMCS dataset captures information documented during a patient visit. It cannot reflect undocumented aspects of the clinician-patient interaction or documentation from previous visits. To our knowledge, there are no studies validating codes physicians use to identify mobility limitations beyond the ICD code specific to ‘impaired mobility’. While our definition was broad, it likely did not capture all diagnoses physicians may use to indicate a mobility limitation. For example, physicians may document impairments such as shortness of breath that may contribute to mobility limitations. Some relevant diagnosis codes in current use were not available prior to 2017, such as the ICD code for sarcopenia. Furthermore, ICD codes are administrative codes primarily used for billing purposes; not all practices will document codes for which there is no reimbursement or relation to ordering diagnostic services even if the physician discusses mobility limitations. However, administrative codes only accounted for 20% of the visits identified as including mobility limitation-related documentation. The transition from ICD-9 to ICD-10 occurred in 2016 and may have impacted our findings. We analyzed our sample and found no statistically significant differences between 2012–2015 and 2016 in mobility limitation-related documentation. The standard error exceeded 30% for some estimates due to the small sample size of visits with mobility limitation documentation (1,430 out of 64,892 total actual visits) and should be interpreted with caution. The dataset groups many physician subspecialties under the umbrella of “primary care,” including physiatrists and geriatricians; these specialists may be the most likely to address mobility limitations, but we cannot assess their independent contributions to the overall prevalence of mobility limitation-related documentation. Multiple categories of missing data (e.g., missing patient primary insurance, missing practice revenue from Medicare, etc.) were statistically significant predictors of mobility limitation documentation; it is difficult to interpret their overall influence, as there is no way to know why the data are missing. Finally, mobility limitations are a complex interplay between biomedical, personal, and environmental factors; further investigation may quantify or qualify other patient-, physician-, or practice-level characteristics influencing physician documentation behaviors.

Conclusions

Mobility limitations are a serious concern for an aging population but are likely under-documented by ambulatory care practitioners. Factors associated with increased odds of mobility limitation documentation include those likely indicative of noticeable changes in physical function. Low overall rates of mobility limitation documentation and documentation of mobility issues once functional limitations are overt have implications for future patient health.

Supplementary Material

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ACNKOWLEDGMENTS

The authors report no conflict of interest. The sponsor played no role in the design, methods, subject recruitment, data collections, analysis, and preparation of paper. Authors’ roles included study concept and design (Shuman, Freburger, Brach), acquisition of data (Shuman and Freburger), analysis and interpretation of data (Shuman, Freburger, Brach, Bean), and preparation of manuscript (Shuman, Freburger, Brach, Bean).

DECLARATIONS OF INTEREST:

This research was supported by Promotion of Doctoral Studies (PODS) I award from the Foundation for Physical Therapy Research and an Adopt-A-Doc Scholarship from the Geriatric Academy of the American Physical Therapy Association to Valerie Shuman. Jenifer S. Brach, PT, PhD, FAPTA was supported by a Midcareer Investigator Award from the National Institute on Aging (K24 AG057728). The authors report no conflicts of interest.

ABBREVIATIONS:

ICD

International Classification of Diseases

NAMCS

National Ambulatory Care Medical Survey

Footnotes

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