- Email: [email protected]
Adherence to Scheduled Therapy Sessions: The Influence of Payer Source
CLINICAL ARTICLE JHT READ
FOR
CREDIT ARTICLE # 100
Adherence to Scheduled Therapy Sessions: The Influence of Payer Source Frank Grispino, MOT, OTR/L, CHT Rehabilitation and Sports Medicine Department, St. Francis Hospital and Health Services, Maryville, Missouri 64468
Phil Messner, EdD Educational Leadership, Northwest Missouri State University, Maryville, Missouri
A common complaint among clinicians and clinicmanagers is that many of their patients have low levels of adherence to scheduled therapy sessions. This can not only be frustrating to providers, but also can adversely impact clinical operations by making it difficult to organize schedules, allocate resources for patient care, and prevent a loss of revenue. There are only a few studies that have characterized adherence and offered some of the possible factors associated with it. Private-pay patients appear to be more likely to not show up for a scheduled appointment than those who were covered by other payer sources.1 With a sample size of 703 and use of logistic regression analysis, it was determined that both payer source and receiving a telephone call before a scheduled This submission was not adapted from a presentation at a meeting. There is no grant support related to this submission. Correspondence and reprint requests to Frank Grispino MOT, OTR/L, CHT, Rehabilitation and Sports Medicine Department, St. Francis Hospital and Health Services, 2016 South Main, Maryville, MO 64468. e-mail:. 0894-1130/$ e see front matter Ó 2008 Hanley & Belfus, an imprint of Elsevier Inc. All rights reserved. doi:10.1197/j.jht.2007.10.023
286
JOURNAL OF HAND THERAPY
ABSTRACT: This study attempted to identify if there was a difference in adherence patterns to scheduled therapy sessions as related to third-party payer-source. Data were gathered over a five-month period and statistically analyzed. A total of 4,552 patient visits constituted the study sample. A statistically significant relationship between third-party payer-source and adherence to scheduled therapy sessions was identified. Patients with Medicare or Workers Compensation as third-party payer-sources had the highest adherence. Patients with Medicaid as a third-party payer-source had the lowest adherence. There was a 20.4% chance that a patient with Medicaid as a payer source and 14.6% chance a private payer would not attend a scheduled therapy session compared to 6% for Medicare and 5.5% for Worker’s Compensation. Facilitation of financial counseling and knowing that billed charges would be written off as charity by the therapy clinic did not increase the likelihood that a patient with Medicaid as a third-party payersource would attend. The phenomenon of inconsistent adherence to scheduled therapy sessions should be taken into account by physicians, therapists, and managers. These inconsistent adherence patterns can negatively affect clinical procedures and outcomes and should be considered when developing treatment and business plans. J HAND THER. 2008;21:286–91.
appointment were independent predictors of adherence to scheduled appointments. Diabetic patients with psychological attachment styles characterized by low levels of collaboration also seem to miss more scheduled primary care appointments than those with secure attachment styles. Additionally, a concurrent diagnosis of depression was found to be a magnifier of this behavior.2 Finally, patients scoring low on self-perceived time utilization skills, as measured by a subscale of Wessman’s Temporal Experience Questionnaire, were twice as likely to miss scheduled appointments in a pediatric clinic as high scorers.3 Evidence was also found that a patient’s adherence with scheduled surgical procedures could be predicted from their adherence with other health care appointments.4 To date, however, it has been difficult to generalize these results to a rural population or a population with lower numbers of insured patients and lower socioeconomic status due to the paucity of information. The purpose of this study was to determine if there was a difference in adherence patterns to scheduled therapy sessions as related to third-party payersource at a Missouri sole community provider hospital-based outpatient/hand clinic.
METHODS
Research questions were written to explore this data set as presented below:
In this prospective case study, data were gathered over a five-month period, from July through October 2005, at a sole community provider hospital-based outpatient rehab clinic in rural Missouri. All patients during the time period were included in the study. A total of 4,552 patient visits constituted the study sample. Participants in this study were from an outpatient population with primarily orthopedic and hand diagnoses. The primary source of data was a handwritten schedule book kept at the clinic reception window. If a patient did not attend a scheduled therapy session, the nonadherence and type of nonadherence were documented on the schedule book beside that patient’s name. Three types of nonadherence were documented by checking one of three columns on the daily log. Each column header represented the type of nonadherence:
Research Question 1. Can a prediction be made as to the likelihood of patients not adhering to scheduled appointments? Research Question 2. Is one payer source more likely to be nonadherent to scheduled appointments than another? Research Question 3. Is there a difference in the type of patient nonadherence behavior by funding source? Research Question 4. Is there a difference in Medicaid patient adherence behavior before and after state Medicaid law change?
d d d
no show/no call cancel without rescheduling cancel with rescheduling.
The same information was documented on the treating therapist’s handwritten daily charge sheet. Office support staff reconciled these data on a daily basis and kept manual tabulation of event type by payer source. Billing software, in place at the research clinic, allowed a tabulation of visit totals by payer source for the study dates. All data were entered into an Excel spreadsheet and statistical analysis was then possible. Changes in Missouri Medicaid law during the study period led researchers to segment the data into ‘‘before’’ and ‘‘after’’ data sets. After the law was changed, occupational and physical therapy services were no longer a financially covered service for Medicaid beneficiaries aged 19 years and older. A process was put in place at the research facility that involved financial counseling before initiation of services. With minimal paperwork completion, the adult Medicaid holder would qualify to have their therapy bill written off as charity by the research institution.
Given the nominal nature of the data set, Chi Square analysis was selected to determine the level of significance at Alpha equal to or less than 0.05. Percentages and frequencies of patient adherence behavior were computed and recorded.
RESULTS Study findings are presented below for the research questions. A summary table of results was constructed for each of the four research questions. This section is organized by research question.
Research Question 1 The authors first addressed the research question ‘‘Can a prediction be made as to the likelihood of patients not adhering to scheduled appointments?’’ A data set consisting of Total Number of Attended Appointments, Total Number of Missed Appointments, and Total Number of Booked Appointments by Funding Source was constructed (see Table 1). Next, a percentage was computed by dividing the Total Missed Appointments by Total Booked Appointments by funding source. This ratio was deemed the ‘‘Percentage of Missed
TABLE 1. Likelihood of Nonadherence to a Scheduled Appointment Percentage and Rank by Funding Source Funding Source Medicare Medicaid Work comp Insurance Private pay Column total
Total Missed App.
Total App. Attended
Total Booked App.
Percentage of Missed App.
63 53 48 245 14 423
994 207 832 2,014 82 4,129
1,057 260 880 2,259 96 4,552
6 20.4 5.5 10.8 14.6 9.3
Nonadherence Likelihood Rank 4 1 5 3 2 Not ranked
Note 1: Patient visitation data are based on five-month time period. Note 2: App. ¼ Appointment; Percentage of Missed App. ¼ Total Missed Appointments within payer source group/Total Booked Appointments within payer source group.
JulyeSeptember 2008 287
Appointments.’’ Then, each percentage was rankordered by funding source with the number one rank given to the funding source with the highest chance of nonadherence. Patients with Medicaid funding were ranked number one, and found to have a 20.4% chance of nonadherence for their scheduled therapy session. Patients with Work Comp had a 5.5% chance of being nonadherent, and given a rank of number five. The average likelihood for all payer sources of missing a booked appointment was 9.3%. These findings led the researchers to investigate further to determine if there was a significant relationship between funding sources and adherence to scheduled appointment patterns.
Research Question 2 Next, the researchers looked at the question ‘‘Is one payer source more likely to be nonadherent to scheduled appointments than another?’’ Percentages were computed by dividing the frequency of missed visits recorded in each third-party payer category by total number of missed appointments overall to attain ‘‘percentage missed.’’ Likewise, the number of appointments made for each payer source was divided by the total number of appointments made to attain ‘‘percentage attended.’’ As shown in Table 2, the highest ‘‘percent attended’’ (48.8%) was reported for patients with private insurance as the funding source. Additionally, patients with Medicaid and private pay as their funding source recorded the lowest percentages of the ‘‘percent attended’’ (5.0% and 2.0%, respectively). Medicare and Work Comp accounted for the remaining office visits. When subjected to Chi Square analysis, a significant difference (x2 (4) ¼ 76.9, p ¼ 7.87 E16) was identified.
appointments not canceled by phone (No Show/No Call); 2) missed appointments but canceled by phone and not rescheduled (Cancel/No Reschedule); and 3) number of missed appointments but canceled and rescheduled by phone (Cancel/Reschedule). The data were then subjected to crosstab Chi Square analysis and the results recorded. As shown in Table 3, significant major differences (x2 (12) ¼ 20.95, p ¼ 0.05) were found by funding source. It was observed that patients with workman’s compensation (2%) and private pay (7%) were less likely to reschedule their visits than other types of funding source patients. Whereas Medicaid patients (45%) were more likely to No Show/No Call, and least likely to Cancel/Reschedule (17%). It was also found that the private payers were more likely to No Show/No Call (79%) than other types of missed appointment behaviors. Medicare patients were most likely to Cancel/No Reschedule (49%) and least likely Cancel/Reschedule (16%).
Research Question 4 The last issue addressed in this study was to determine the impact of Medicaid law change on Medicaid patient adherence behavior. The number of patient-booked appointments and the number of appointments missed before and after changes in the Missouri Medicaid law change were recorded. As shown in Table 4, the percentage of missed Medicaid-funded appointments were about the same before (19.7%) and after (21.2%) state Medicaid law change. There was no significant relationship (x 2 (1) ¼ 0.86, p ¼ 0.77). These findings suggest that changes in Medicaid state law and initiation of financial counseling/charity write-off procedures did not change patient adherence behavior.
Research Question 3
DISCUSSION
The authors then looked at question number 3, ‘‘Is there a difference in the type of patient nonadherence behavior by funding source?’’ The data were categorized by three different types of patient nonadherence behavior: 1) missed
In this study, there were significant differences in adherence to scheduled therapy sessions as viewed by payer source. Medicaid and private payer sources were the two groups with the highest chance of being nonadherent to a scheduled appointment. Knowing
TABLE 2. Chi Square Analysis Results of Nonadherence by Funding Source App. Missed Source Medicare Medicaid Work company Insurance Private pay Total
App. Attended
Number
Percent
Total
Percent
63 53 48 245 14 423
14.9 12.5 11.3 57.9 3.3 100
994 207 832 2,014 82 4,129
24.1 5.0 20.2 48.8 2.0 100
Note 1: Total number of appointments booked during five-month period ¼ 4552. Note 2: p , 0.001; Reject the Null Hypothesis.
288
JOURNAL OF HAND THERAPY
Chi Square
df
p
76.9
4
7.87 E16
TABLE 3. Summary Type of Nonadherence Behavior Results by Funding Source Funding Source Medicare Medicaid Work company Insurance Private pay
No Show/No Call 22 24 19 81 11
Cancel/No Reschedule
(35%) (45%) (40%) (33%) (79%)
31 20 28 130 2
(49%) (38%) (58%) (53%) (14%)
Cancel Reschedule
Total Missed App.
10 (16%) 9 (17%) 1 (2%) 34 (14%) 1 (7%)
63 53 48 245 14
Chi Square
df
p
20.95
12
0.05*
Note 1: Row percents are reported. Note 2: *Significant p # 0.05; reject null hypothesis.
that low adherence to scheduled therapy sessions can be correlated to payer source can have value. The implications for practice of these findings are twofold. The first implication falls into the realm of patient compliance. Complex surgical procedures often require complex and/or consistent therapeutic intervention. Timelines of progression are often based on the science of tissue-healing timelines. Other approaches describe the benefits of tailoring progression as related to individualized tissue response. Current literature in tendon repair rehabilitation is an example of this developing school of thought.5 Regardless of which philosophy is followed, consistent therapist evaluation and guidance is needed. Commonly, the treating therapist uses formal therapy sessions as a time to reassess the appropriateness of progression, maintaining, or regressing interventions and home exercise programs within the continuum of treatment. A slower-than-desired clinical progression can have detrimental physical and functional results. Negative effects of immobilization on multiple tissues are well documented.6 From the other side of the continuum, if the patient progresses too quickly without therapist guidance, surgical repairs can be compromised or inflammatory processes can be exacerbated.7 Whether progression is too slow or too fast because of inconsistent adherence to scheduled therapy sessions, the end result could be a less than optimal return of function after injury or surgical procedure. Postsurgical compliance with a therapeutic program could understandably be a factor in a surgeon’s decision-making process when choosing procedures and techniques with some diagnoses and some patients. The second realm of practice implication involves the assignment of limited resources in practice
settings that may have more demands than resources. Time may be the most valuable resource a clinic has, and lost time cannot be replaced. Time scheduled for a patient who does not show up for a scheduled treatment session or evaluation could have been better spent treating another patient who was in need and adherent with attending scheduled appointments. The financial implications are obvious. A therapist can always find activities to fill unexpected downtime, but lost revenues are not commensurate with exceptional financial performance of a clinic. Attention to stewardship is needed to maintain operations of a clinic, and cannot be ignored if a clinic desires to keep their doors open and treat those in need. Telephone reminders have been reported to increase the likelihood of attending scheduled visits in a hospital-based adolescent medical clinic by 47.8%,1 and may be beneficial in the rehabilitation setting. A practice of scheduling patients with a higher chance of not showing up to a scheduled surgical procedure at the end of the day to maximize operating room utilization was discussed in the literature,4 and may also have merit in the rehabilitation setting. The significant amount of missed therapy sessions must be taken into account when developing a treatment plan or business plan if treating Medicaid and private pay patients. Inconsistent adherence to scheduled therapy sessions is a real issue and affects therapists, physicians, managers, and the patients themselves.
CONCLUSIONS In this study, a nonfinancial obligation did not increase adherence to scheduled therapy sessions in
TABLE 4. Summary Chi Square Analysis Results: Nonadherence Before and After Change in Medicaid Law Before Law Change Source
After Law Change
n
% of Total
n
% of Total
Medicaid attended Not attended
114 28
80.3 19.7
93 25
78.8 21.2
Total
142
100.0
118
100.0
Chi Square
df
p
0.86
1
0.77*
*Not significant; accept the null hypothesis.
JulyeSeptember 2008 289
Medicaid patients. Knowledge of this level of attendance should initiate the development of practices aimed to mitigate this behavior, and should be backed up by analysis to assess effectiveness of preventative measures.
REFERENCES 1. O’Brien G, Lazebnik R. Telephone call reminders and attendance in an adolescent clinic. Pediatrics. 1998;101:e6. 2. Ciechanowski P, Russo J, Katon W, et al. Where is the patient? The association of psychosocial factors and missed primary care appointments in patients with diabetes. Gen Hosp Psychiatry. 2006;28:9–17.
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JOURNAL OF HAND THERAPY
3. Gerson L, McCord G, Wiggins S. A strategy to increase appointment keeping in a pediatric clinic. J Community Health. 1986;11: 111–21. 4. Basson M, Butler T, Verma H. Predicting patient nonappearance for surgery as a scheduling strategy to optimize operating room utilization in a veterans’ administration hospital. Anesthesiology. 2006;104:826–34. 5. Groth G. Pyramid of progressive force exercises to the injured flexor tendon. J Hand Ther. 2004;17:31–42. 6. Olson V. Connective tissue response to injury, immobilization, mobilization. Home study course 11.2.1. In: Wadsworth C (ed). Current Concepts of Orthopedic Physical Therapy. La Crosse, WI: Orthopaedic Section, APTA, Inc., 2001. 7. Evans R. Clinical management of extensor tendon injuries. In: Hunter J, Mackin E, Callahan A (eds). Rehabilitation of the Hand and Upper Extremities. 5th ed. St. Louis, MO: Mosby, Inc., 2002, pp 542–79.
JHT Read for Credit Quiz: Article # 100
Record your answers on the Return Answer Form found on the tear-out coupon at the back of this issue. There is only one best answer for each question. #1. The adherence pattern seen was a. Medicaid & Workers Comp best b. Medicare & Medicaid best c. Medicaid worst, Medicare & Workers Comp best d. Workers Comp worst #2. The chance that a private paying patient would not attend a scheduled visit was approximately a. 15% b. 20% c. 25% d. 30% #3. Those least likely to reschedule missed visits were
a. Medicaid b. Medicare c. geriatrics d. workers comp & private pay #4. In the Workers Comp group the most common pattern of missed appointments was a. no show b. cancel & reschedule c. cancel & no-reschedule d. arrived for visit on the wrong day #5. Changes in the state Medicaid law had a significant effect on adherence patterns a. true b. false When submitting to the HTCC for re-certification, please batch your JHT RFC certificates in groups of 3 or more to get full credit.
JulyeSeptember 2008 291
FOR
CREDIT ARTICLE # 100
Adherence to Scheduled Therapy Sessions: The Influence of Payer Source Frank Grispino, MOT, OTR/L, CHT Rehabilitation and Sports Medicine Department, St. Francis Hospital and Health Services, Maryville, Missouri 64468
Phil Messner, EdD Educational Leadership, Northwest Missouri State University, Maryville, Missouri
A common complaint among clinicians and clinicmanagers is that many of their patients have low levels of adherence to scheduled therapy sessions. This can not only be frustrating to providers, but also can adversely impact clinical operations by making it difficult to organize schedules, allocate resources for patient care, and prevent a loss of revenue. There are only a few studies that have characterized adherence and offered some of the possible factors associated with it. Private-pay patients appear to be more likely to not show up for a scheduled appointment than those who were covered by other payer sources.1 With a sample size of 703 and use of logistic regression analysis, it was determined that both payer source and receiving a telephone call before a scheduled This submission was not adapted from a presentation at a meeting. There is no grant support related to this submission. Correspondence and reprint requests to Frank Grispino MOT, OTR/L, CHT, Rehabilitation and Sports Medicine Department, St. Francis Hospital and Health Services, 2016 South Main, Maryville, MO 64468. e-mail:
286
JOURNAL OF HAND THERAPY
ABSTRACT: This study attempted to identify if there was a difference in adherence patterns to scheduled therapy sessions as related to third-party payer-source. Data were gathered over a five-month period and statistically analyzed. A total of 4,552 patient visits constituted the study sample. A statistically significant relationship between third-party payer-source and adherence to scheduled therapy sessions was identified. Patients with Medicare or Workers Compensation as third-party payer-sources had the highest adherence. Patients with Medicaid as a third-party payer-source had the lowest adherence. There was a 20.4% chance that a patient with Medicaid as a payer source and 14.6% chance a private payer would not attend a scheduled therapy session compared to 6% for Medicare and 5.5% for Worker’s Compensation. Facilitation of financial counseling and knowing that billed charges would be written off as charity by the therapy clinic did not increase the likelihood that a patient with Medicaid as a third-party payersource would attend. The phenomenon of inconsistent adherence to scheduled therapy sessions should be taken into account by physicians, therapists, and managers. These inconsistent adherence patterns can negatively affect clinical procedures and outcomes and should be considered when developing treatment and business plans. J HAND THER. 2008;21:286–91.
appointment were independent predictors of adherence to scheduled appointments. Diabetic patients with psychological attachment styles characterized by low levels of collaboration also seem to miss more scheduled primary care appointments than those with secure attachment styles. Additionally, a concurrent diagnosis of depression was found to be a magnifier of this behavior.2 Finally, patients scoring low on self-perceived time utilization skills, as measured by a subscale of Wessman’s Temporal Experience Questionnaire, were twice as likely to miss scheduled appointments in a pediatric clinic as high scorers.3 Evidence was also found that a patient’s adherence with scheduled surgical procedures could be predicted from their adherence with other health care appointments.4 To date, however, it has been difficult to generalize these results to a rural population or a population with lower numbers of insured patients and lower socioeconomic status due to the paucity of information. The purpose of this study was to determine if there was a difference in adherence patterns to scheduled therapy sessions as related to third-party payersource at a Missouri sole community provider hospital-based outpatient/hand clinic.
METHODS
Research questions were written to explore this data set as presented below:
In this prospective case study, data were gathered over a five-month period, from July through October 2005, at a sole community provider hospital-based outpatient rehab clinic in rural Missouri. All patients during the time period were included in the study. A total of 4,552 patient visits constituted the study sample. Participants in this study were from an outpatient population with primarily orthopedic and hand diagnoses. The primary source of data was a handwritten schedule book kept at the clinic reception window. If a patient did not attend a scheduled therapy session, the nonadherence and type of nonadherence were documented on the schedule book beside that patient’s name. Three types of nonadherence were documented by checking one of three columns on the daily log. Each column header represented the type of nonadherence:
Research Question 1. Can a prediction be made as to the likelihood of patients not adhering to scheduled appointments? Research Question 2. Is one payer source more likely to be nonadherent to scheduled appointments than another? Research Question 3. Is there a difference in the type of patient nonadherence behavior by funding source? Research Question 4. Is there a difference in Medicaid patient adherence behavior before and after state Medicaid law change?
d d d
no show/no call cancel without rescheduling cancel with rescheduling.
The same information was documented on the treating therapist’s handwritten daily charge sheet. Office support staff reconciled these data on a daily basis and kept manual tabulation of event type by payer source. Billing software, in place at the research clinic, allowed a tabulation of visit totals by payer source for the study dates. All data were entered into an Excel spreadsheet and statistical analysis was then possible. Changes in Missouri Medicaid law during the study period led researchers to segment the data into ‘‘before’’ and ‘‘after’’ data sets. After the law was changed, occupational and physical therapy services were no longer a financially covered service for Medicaid beneficiaries aged 19 years and older. A process was put in place at the research facility that involved financial counseling before initiation of services. With minimal paperwork completion, the adult Medicaid holder would qualify to have their therapy bill written off as charity by the research institution.
Given the nominal nature of the data set, Chi Square analysis was selected to determine the level of significance at Alpha equal to or less than 0.05. Percentages and frequencies of patient adherence behavior were computed and recorded.
RESULTS Study findings are presented below for the research questions. A summary table of results was constructed for each of the four research questions. This section is organized by research question.
Research Question 1 The authors first addressed the research question ‘‘Can a prediction be made as to the likelihood of patients not adhering to scheduled appointments?’’ A data set consisting of Total Number of Attended Appointments, Total Number of Missed Appointments, and Total Number of Booked Appointments by Funding Source was constructed (see Table 1). Next, a percentage was computed by dividing the Total Missed Appointments by Total Booked Appointments by funding source. This ratio was deemed the ‘‘Percentage of Missed
TABLE 1. Likelihood of Nonadherence to a Scheduled Appointment Percentage and Rank by Funding Source Funding Source Medicare Medicaid Work comp Insurance Private pay Column total
Total Missed App.
Total App. Attended
Total Booked App.
Percentage of Missed App.
63 53 48 245 14 423
994 207 832 2,014 82 4,129
1,057 260 880 2,259 96 4,552
6 20.4 5.5 10.8 14.6 9.3
Nonadherence Likelihood Rank 4 1 5 3 2 Not ranked
Note 1: Patient visitation data are based on five-month time period. Note 2: App. ¼ Appointment; Percentage of Missed App. ¼ Total Missed Appointments within payer source group/Total Booked Appointments within payer source group.
JulyeSeptember 2008 287
Appointments.’’ Then, each percentage was rankordered by funding source with the number one rank given to the funding source with the highest chance of nonadherence. Patients with Medicaid funding were ranked number one, and found to have a 20.4% chance of nonadherence for their scheduled therapy session. Patients with Work Comp had a 5.5% chance of being nonadherent, and given a rank of number five. The average likelihood for all payer sources of missing a booked appointment was 9.3%. These findings led the researchers to investigate further to determine if there was a significant relationship between funding sources and adherence to scheduled appointment patterns.
Research Question 2 Next, the researchers looked at the question ‘‘Is one payer source more likely to be nonadherent to scheduled appointments than another?’’ Percentages were computed by dividing the frequency of missed visits recorded in each third-party payer category by total number of missed appointments overall to attain ‘‘percentage missed.’’ Likewise, the number of appointments made for each payer source was divided by the total number of appointments made to attain ‘‘percentage attended.’’ As shown in Table 2, the highest ‘‘percent attended’’ (48.8%) was reported for patients with private insurance as the funding source. Additionally, patients with Medicaid and private pay as their funding source recorded the lowest percentages of the ‘‘percent attended’’ (5.0% and 2.0%, respectively). Medicare and Work Comp accounted for the remaining office visits. When subjected to Chi Square analysis, a significant difference (x2 (4) ¼ 76.9, p ¼ 7.87 E16) was identified.
appointments not canceled by phone (No Show/No Call); 2) missed appointments but canceled by phone and not rescheduled (Cancel/No Reschedule); and 3) number of missed appointments but canceled and rescheduled by phone (Cancel/Reschedule). The data were then subjected to crosstab Chi Square analysis and the results recorded. As shown in Table 3, significant major differences (x2 (12) ¼ 20.95, p ¼ 0.05) were found by funding source. It was observed that patients with workman’s compensation (2%) and private pay (7%) were less likely to reschedule their visits than other types of funding source patients. Whereas Medicaid patients (45%) were more likely to No Show/No Call, and least likely to Cancel/Reschedule (17%). It was also found that the private payers were more likely to No Show/No Call (79%) than other types of missed appointment behaviors. Medicare patients were most likely to Cancel/No Reschedule (49%) and least likely Cancel/Reschedule (16%).
Research Question 4 The last issue addressed in this study was to determine the impact of Medicaid law change on Medicaid patient adherence behavior. The number of patient-booked appointments and the number of appointments missed before and after changes in the Missouri Medicaid law change were recorded. As shown in Table 4, the percentage of missed Medicaid-funded appointments were about the same before (19.7%) and after (21.2%) state Medicaid law change. There was no significant relationship (x 2 (1) ¼ 0.86, p ¼ 0.77). These findings suggest that changes in Medicaid state law and initiation of financial counseling/charity write-off procedures did not change patient adherence behavior.
Research Question 3
DISCUSSION
The authors then looked at question number 3, ‘‘Is there a difference in the type of patient nonadherence behavior by funding source?’’ The data were categorized by three different types of patient nonadherence behavior: 1) missed
In this study, there were significant differences in adherence to scheduled therapy sessions as viewed by payer source. Medicaid and private payer sources were the two groups with the highest chance of being nonadherent to a scheduled appointment. Knowing
TABLE 2. Chi Square Analysis Results of Nonadherence by Funding Source App. Missed Source Medicare Medicaid Work company Insurance Private pay Total
App. Attended
Number
Percent
Total
Percent
63 53 48 245 14 423
14.9 12.5 11.3 57.9 3.3 100
994 207 832 2,014 82 4,129
24.1 5.0 20.2 48.8 2.0 100
Note 1: Total number of appointments booked during five-month period ¼ 4552. Note 2: p , 0.001; Reject the Null Hypothesis.
288
JOURNAL OF HAND THERAPY
Chi Square
df
p
76.9
4
7.87 E16
TABLE 3. Summary Type of Nonadherence Behavior Results by Funding Source Funding Source Medicare Medicaid Work company Insurance Private pay
No Show/No Call 22 24 19 81 11
Cancel/No Reschedule
(35%) (45%) (40%) (33%) (79%)
31 20 28 130 2
(49%) (38%) (58%) (53%) (14%)
Cancel Reschedule
Total Missed App.
10 (16%) 9 (17%) 1 (2%) 34 (14%) 1 (7%)
63 53 48 245 14
Chi Square
df
p
20.95
12
0.05*
Note 1: Row percents are reported. Note 2: *Significant p # 0.05; reject null hypothesis.
that low adherence to scheduled therapy sessions can be correlated to payer source can have value. The implications for practice of these findings are twofold. The first implication falls into the realm of patient compliance. Complex surgical procedures often require complex and/or consistent therapeutic intervention. Timelines of progression are often based on the science of tissue-healing timelines. Other approaches describe the benefits of tailoring progression as related to individualized tissue response. Current literature in tendon repair rehabilitation is an example of this developing school of thought.5 Regardless of which philosophy is followed, consistent therapist evaluation and guidance is needed. Commonly, the treating therapist uses formal therapy sessions as a time to reassess the appropriateness of progression, maintaining, or regressing interventions and home exercise programs within the continuum of treatment. A slower-than-desired clinical progression can have detrimental physical and functional results. Negative effects of immobilization on multiple tissues are well documented.6 From the other side of the continuum, if the patient progresses too quickly without therapist guidance, surgical repairs can be compromised or inflammatory processes can be exacerbated.7 Whether progression is too slow or too fast because of inconsistent adherence to scheduled therapy sessions, the end result could be a less than optimal return of function after injury or surgical procedure. Postsurgical compliance with a therapeutic program could understandably be a factor in a surgeon’s decision-making process when choosing procedures and techniques with some diagnoses and some patients. The second realm of practice implication involves the assignment of limited resources in practice
settings that may have more demands than resources. Time may be the most valuable resource a clinic has, and lost time cannot be replaced. Time scheduled for a patient who does not show up for a scheduled treatment session or evaluation could have been better spent treating another patient who was in need and adherent with attending scheduled appointments. The financial implications are obvious. A therapist can always find activities to fill unexpected downtime, but lost revenues are not commensurate with exceptional financial performance of a clinic. Attention to stewardship is needed to maintain operations of a clinic, and cannot be ignored if a clinic desires to keep their doors open and treat those in need. Telephone reminders have been reported to increase the likelihood of attending scheduled visits in a hospital-based adolescent medical clinic by 47.8%,1 and may be beneficial in the rehabilitation setting. A practice of scheduling patients with a higher chance of not showing up to a scheduled surgical procedure at the end of the day to maximize operating room utilization was discussed in the literature,4 and may also have merit in the rehabilitation setting. The significant amount of missed therapy sessions must be taken into account when developing a treatment plan or business plan if treating Medicaid and private pay patients. Inconsistent adherence to scheduled therapy sessions is a real issue and affects therapists, physicians, managers, and the patients themselves.
CONCLUSIONS In this study, a nonfinancial obligation did not increase adherence to scheduled therapy sessions in
TABLE 4. Summary Chi Square Analysis Results: Nonadherence Before and After Change in Medicaid Law Before Law Change Source
After Law Change
n
% of Total
n
% of Total
Medicaid attended Not attended
114 28
80.3 19.7
93 25
78.8 21.2
Total
142
100.0
118
100.0
Chi Square
df
p
0.86
1
0.77*
*Not significant; accept the null hypothesis.
JulyeSeptember 2008 289
Medicaid patients. Knowledge of this level of attendance should initiate the development of practices aimed to mitigate this behavior, and should be backed up by analysis to assess effectiveness of preventative measures.
REFERENCES 1. O’Brien G, Lazebnik R. Telephone call reminders and attendance in an adolescent clinic. Pediatrics. 1998;101:e6. 2. Ciechanowski P, Russo J, Katon W, et al. Where is the patient? The association of psychosocial factors and missed primary care appointments in patients with diabetes. Gen Hosp Psychiatry. 2006;28:9–17.
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JOURNAL OF HAND THERAPY
3. Gerson L, McCord G, Wiggins S. A strategy to increase appointment keeping in a pediatric clinic. J Community Health. 1986;11: 111–21. 4. Basson M, Butler T, Verma H. Predicting patient nonappearance for surgery as a scheduling strategy to optimize operating room utilization in a veterans’ administration hospital. Anesthesiology. 2006;104:826–34. 5. Groth G. Pyramid of progressive force exercises to the injured flexor tendon. J Hand Ther. 2004;17:31–42. 6. Olson V. Connective tissue response to injury, immobilization, mobilization. Home study course 11.2.1. In: Wadsworth C (ed). Current Concepts of Orthopedic Physical Therapy. La Crosse, WI: Orthopaedic Section, APTA, Inc., 2001. 7. Evans R. Clinical management of extensor tendon injuries. In: Hunter J, Mackin E, Callahan A (eds). Rehabilitation of the Hand and Upper Extremities. 5th ed. St. Louis, MO: Mosby, Inc., 2002, pp 542–79.
JHT Read for Credit Quiz: Article # 100
Record your answers on the Return Answer Form found on the tear-out coupon at the back of this issue. There is only one best answer for each question. #1. The adherence pattern seen was a. Medicaid & Workers Comp best b. Medicare & Medicaid best c. Medicaid worst, Medicare & Workers Comp best d. Workers Comp worst #2. The chance that a private paying patient would not attend a scheduled visit was approximately a. 15% b. 20% c. 25% d. 30% #3. Those least likely to reschedule missed visits were
a. Medicaid b. Medicare c. geriatrics d. workers comp & private pay #4. In the Workers Comp group the most common pattern of missed appointments was a. no show b. cancel & reschedule c. cancel & no-reschedule d. arrived for visit on the wrong day #5. Changes in the state Medicaid law had a significant effect on adherence patterns a. true b. false When submitting to the HTCC for re-certification, please batch your JHT RFC certificates in groups of 3 or more to get full credit.
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