Technology for primary care — terrific, terrifying, or both?

We have all been using technology in our primary care practices for a long time but newer formats have been emerging so fast that our minds, much less our staff’s minds, may be spinning.

Our old friend the telephone, a time-soaking nemesis for scheduling, checking coverage, questions calls, prescribing, quick consults, and follow-up is being replaced by EHR portals and SMS for messaging (e.g. DoctorConnect, SimplePractice), drop-in televisits and patient education links on our websites (e.g. Schmitt Pediatric Care, Remedy Connect), and chatbots for scheduling (e.g. CHEC-UP). While time is saved, what is lost may be hearing the subtext of anxiety or misperceptions in parents’ voices that would change our advice and the empathetic human connection in conversations with our patients. A hybrid approach may be better.

The paper appointment book has been replaced by scheduling systems sometimes lacking in flexibility for double booking, sibling visits, and variable length or extremely valuable multi-professional visits. Allowing patients to book their own visits may place complex problems in inappropriate slots, so only allowing online requests for visits is safer. On the other hand, many of us can now squeeze in “same day” televisits (e.g. Blueberry Pediatrics), sometimes from outside our practice (e.g., zocdoc), to increase payments and even entice new patients to enroll.

Amazing advances in technology are being made in specialty care such as genetic modifications (CRISPR), immunotherapies (mRNA vaccines and AI drug design), robot-assisted surgery, and 3-D printing of body parts and prosthetics. Technology as treatment such as transcranial magnetic stimulation and vagal stimulation are finding value in psychiatry.

But beside being aware of and able to order such specialty technologies, innovations are now extending our senses in primary care such as amplified or visual stethoscopes, bedside ultrasound (e.g. Butterfly), remote visualization (oto-, endo-)scopes, photographic vision screens (e.g. iScreen) for skin lesion (VisualDx) and genetic syndrome facial recognition. We need to be sure that technologies are tested and calibrated for children and different racial groups and genders to provide safe and equitable care. Early adoption may not always be the best approach. Costs of technology, as usual, may limit access to these advanced care aids especially, as usual, in practices serving low income and rural communities.

Patients, especially younger parents and youth, now expect to participate and can directly benefit from technology as part of their health care. Validated parent or self-report screens (e.g. EHRs, Phreesia) can detect important issues early for more effective intervention. Such questionnaires typically provide a pass/fail result or score, but other delivery systems (e.g. CHADIS) include interpretation, assist patients/parents in setting visit priorities and health goals, and even chain results of one questionnaire to secondary screens to hone in on problems, sometimes obviating a time-consuming second visit. Patient-completed comprehensive questionnaires (e.g. Well Visit Planner, CHADIS) allow us time to use our skills to focus on concerns, education, and management rather than asking myriad routine questions. Some (e.g. CHADIS) even create visit documentation reducing our “pajama time” write ups (and burnout); automate repeated online measures to track progress; and use questionnaire results to trigger related patient-specific education and resources rather than the often-ignored generic EHR handouts.

Digital therapeutics such as apps for anxiety (e.g. Calm), depression (e.g. SparkRx, Cass), weight control (e.g. Noom, Lose it), fitness, or sleep tracking (e.g. Whoop) help educate and, in some cases, provide real-time feedback to personalize discovery of contributing factors in order to maintain motivation for positive health behavior change. Some video games improve ADHD symptoms (e.g. EndeavorRX). Virtual reality scenarios have been shown to desensitize those with PTSD and social anxiety or teach social skills to children with autism.

Systems that trigger resource listings (including apps) from screen results can help, but now with over 10,000 apps for mental health, knowing what to recommend for what conditions is a challenge for which ratings (e.g. MINDapps.org) can help. With few product reps visiting to tell us what’s new, we need to read critically about innovations, search the web, subscribe to the AAP SOAPM LISTSERV, visit exhibitors at professional meetings, and talk with peers.

All the digital data collected from health care technology, if assembled with privacy constraints and analyzed with advanced statistical methods, have the possibility, with or without inclusion of genomic data, to allow for more accurate diagnostic and treatment decision support. While AI can search widely for patterns, it needs to be “trained” on appropriate data to make correct conclusions. We are all aware that the history determines 85% of both diagnosis and treatment decisions, particularly in primary care where x-rays or lab tests are not often needed.

But history in EHR notes is often idiosyncratic, entered hours after the visit by the clinician, and does not include the information needed to define diagnostic or guideline criteria, even if the clinician knows and considered those criteria. EHR templates are presented blank and are onerous and time consuming for clinicians. In addition, individual patient barriers to care, preferences, and environmental or subjective concerns are infrequently documented even though they may make the biggest difference to adherence and/or outcomes.

Notes made from voice to text digital AI translation of the encounter (e.g. Nuance DAX) are even less likely to include diagnostic criteria as it would be inappropriate to speak these. To use EHR history data to train AI and to test efficacy of care using variations of guidelines, guideline-related data is needed from online patient entries in questionnaires that are transformed to fill in templates along with some structured choices for clinician entries forming visit notes (e.g. CHADIS). New apps to facilitate clinician documentation of guidelines (e.g. AvoMD) could streamline visits as well as help document guideline criteria. The resulting combination of guideline-relevant patient histories and objective data to test and iteratively refine guidelines will allow a process known as a “Learning Health System.”

Technology to collect this kind of data can allow for the aspirational American Academy of Pediatrics CHILD Registry to approach this goal. Population-level data can provide surveillance for illness, toxins, effects of climate change, social drivers of health, and even effects of technologies themselves such as social media and remote learning so that we can attempt to make the best choices for the future.

Clinicians, staff, and patients will need to develop trust in technology as it infiltrates all aspects of health care. Professionals need both evidence and experience to trust a technology, which takes time and effort. Disinformation in the media may reduce trust or evoke unwarranted trust, as we have all seen regarding vaccines. Clear and coherent public health messaging can help but is no longer a panacea for developing trust in health care. Our nonjudgmental listening and informed opinions are needed more than ever.

The biggest issues for new technology are likely to be the need for workflow adjustments, changing our habit patterns, training, and cost/benefit analyses. With today’s high staff churn, confusion and even chaos can ensue when adopting new technology.

Staff need to be part of the selection process, if at all possible, and discuss how roles and flow will need to change. Having one staff member be a champion and expert for new tech can move adoption to a shared process rather than imposing “one more thing.” It is crucial to discuss the benefits for patients and staff even if the change is required. Sometimes cost savings can include a bonus for staff or free group lunches. Providing a certificate of achievement or title promotion for mastering new tech may be appropriate. Giving some time off from other tasks to learn new workflows can reduce resistance rather than just adding it on to a regular workload. Office “huddles” going forward can include examples of benefits staff have observed or heard about from the adoption. There are quality improvement processes that engage the team — some that earn MOC-4 or CEU credits — that apply to making workflow changes and measuring them iteratively.

If technology takes over important aspects of the work of medical professionals, even if it is faster and/or more accurate, it may degrade clinical observational, interactional, and decision-making skills through lack of use. It may also remove the sense of self-efficacy that motivates professionals to endure onerous training and desire to enter the field. Using technology may reduce empathetic interactions that are basic to humanistic motivation, work satisfaction, and even community respect. Moral injury is already rampant in medicine from restrictions on freedom to do what we see as important for our patients. Technology has great potential and already is enhancing our ability to provide the best care for patients but the risks need to be watched for and ameliorated.

When technology automates comprehensive visit documentation that highlights priority and risk areas from patient input and individualizes decision support, it can facilitate the personalized care that we and our patients want to experience. We must not be so awed, intrigued, or wary of new technology to miss its benefits nor give up our good clinical judgment about the technology or about our patients.

Dr. Howard is assistant professor of pediatrics at The Johns Hopkins University School of Medicine, Baltimore, and creator of CHADIS. She had no other relevant disclosures. Dr. Howard’s contribution to this publication was as a paid expert to MDedge News. E-mail her at pdnews@mdedge.com.

We have all been using technology in our primary care practices for a long time but newer formats have been emerging so fast that our minds, much less our staff’s minds, may be spinning.

Our old friend the telephone, a time-soaking nemesis for scheduling, checking coverage, questions calls, prescribing, quick consults, and follow-up is being replaced by EHR portals and SMS for messaging (e.g. DoctorConnect, SimplePractice), drop-in televisits and patient education links on our websites (e.g. Schmitt Pediatric Care, Remedy Connect), and chatbots for scheduling (e.g. CHEC-UP). While time is saved, what is lost may be hearing the subtext of anxiety or misperceptions in parents’ voices that would change our advice and the empathetic human connection in conversations with our patients. A hybrid approach may be better.

The paper appointment book has been replaced by scheduling systems sometimes lacking in flexibility for double booking, sibling visits, and variable length or extremely valuable multi-professional visits. Allowing patients to book their own visits may place complex problems in inappropriate slots, so only allowing online requests for visits is safer. On the other hand, many of us can now squeeze in “same day” televisits (e.g. Blueberry Pediatrics), sometimes from outside our practice (e.g., zocdoc), to increase payments and even entice new patients to enroll.

Amazing advances in technology are being made in specialty care such as genetic modifications (CRISPR), immunotherapies (mRNA vaccines and AI drug design), robot-assisted surgery, and 3-D printing of body parts and prosthetics. Technology as treatment such as transcranial magnetic stimulation and vagal stimulation are finding value in psychiatry.

But beside being aware of and able to order such specialty technologies, innovations are now extending our senses in primary care such as amplified or visual stethoscopes, bedside ultrasound (e.g. Butterfly), remote visualization (oto-, endo-)scopes, photographic vision screens (e.g. iScreen) for skin lesion (VisualDx) and genetic syndrome facial recognition. We need to be sure that technologies are tested and calibrated for children and different racial groups and genders to provide safe and equitable care. Early adoption may not always be the best approach. Costs of technology, as usual, may limit access to these advanced care aids especially, as usual, in practices serving low income and rural communities.

Patients, especially younger parents and youth, now expect to participate and can directly benefit from technology as part of their health care. Validated parent or self-report screens (e.g. EHRs, Phreesia) can detect important issues early for more effective intervention. Such questionnaires typically provide a pass/fail result or score, but other delivery systems (e.g. CHADIS) include interpretation, assist patients/parents in setting visit priorities and health goals, and even chain results of one questionnaire to secondary screens to hone in on problems, sometimes obviating a time-consuming second visit. Patient-completed comprehensive questionnaires (e.g. Well Visit Planner, CHADIS) allow us time to use our skills to focus on concerns, education, and management rather than asking myriad routine questions. Some (e.g. CHADIS) even create visit documentation reducing our “pajama time” write ups (and burnout); automate repeated online measures to track progress; and use questionnaire results to trigger related patient-specific education and resources rather than the often-ignored generic EHR handouts.

Digital therapeutics such as apps for anxiety (e.g. Calm), depression (e.g. SparkRx, Cass), weight control (e.g. Noom, Lose it), fitness, or sleep tracking (e.g. Whoop) help educate and, in some cases, provide real-time feedback to personalize discovery of contributing factors in order to maintain motivation for positive health behavior change. Some video games improve ADHD symptoms (e.g. EndeavorRX). Virtual reality scenarios have been shown to desensitize those with PTSD and social anxiety or teach social skills to children with autism.

Systems that trigger resource listings (including apps) from screen results can help, but now with over 10,000 apps for mental health, knowing what to recommend for what conditions is a challenge for which ratings (e.g. MINDapps.org) can help. With few product reps visiting to tell us what’s new, we need to read critically about innovations, search the web, subscribe to the AAP SOAPM LISTSERV, visit exhibitors at professional meetings, and talk with peers.

All the digital data collected from health care technology, if assembled with privacy constraints and analyzed with advanced statistical methods, have the possibility, with or without inclusion of genomic data, to allow for more accurate diagnostic and treatment decision support. While AI can search widely for patterns, it needs to be “trained” on appropriate data to make correct conclusions. We are all aware that the history determines 85% of both diagnosis and treatment decisions, particularly in primary care where x-rays or lab tests are not often needed.

But history in EHR notes is often idiosyncratic, entered hours after the visit by the clinician, and does not include the information needed to define diagnostic or guideline criteria, even if the clinician knows and considered those criteria. EHR templates are presented blank and are onerous and time consuming for clinicians. In addition, individual patient barriers to care, preferences, and environmental or subjective concerns are infrequently documented even though they may make the biggest difference to adherence and/or outcomes.

Notes made from voice to text digital AI translation of the encounter (e.g. Nuance DAX) are even less likely to include diagnostic criteria as it would be inappropriate to speak these. To use EHR history data to train AI and to test efficacy of care using variations of guidelines, guideline-related data is needed from online patient entries in questionnaires that are transformed to fill in templates along with some structured choices for clinician entries forming visit notes (e.g. CHADIS). New apps to facilitate clinician documentation of guidelines (e.g. AvoMD) could streamline visits as well as help document guideline criteria. The resulting combination of guideline-relevant patient histories and objective data to test and iteratively refine guidelines will allow a process known as a “Learning Health System.”

Technology to collect this kind of data can allow for the aspirational American Academy of Pediatrics CHILD Registry to approach this goal. Population-level data can provide surveillance for illness, toxins, effects of climate change, social drivers of health, and even effects of technologies themselves such as social media and remote learning so that we can attempt to make the best choices for the future.

Clinicians, staff, and patients will need to develop trust in technology as it infiltrates all aspects of health care. Professionals need both evidence and experience to trust a technology, which takes time and effort. Disinformation in the media may reduce trust or evoke unwarranted trust, as we have all seen regarding vaccines. Clear and coherent public health messaging can help but is no longer a panacea for developing trust in health care. Our nonjudgmental listening and informed opinions are needed more than ever.

The biggest issues for new technology are likely to be the need for workflow adjustments, changing our habit patterns, training, and cost/benefit analyses. With today’s high staff churn, confusion and even chaos can ensue when adopting new technology.

Staff need to be part of the selection process, if at all possible, and discuss how roles and flow will need to change. Having one staff member be a champion and expert for new tech can move adoption to a shared process rather than imposing “one more thing.” It is crucial to discuss the benefits for patients and staff even if the change is required. Sometimes cost savings can include a bonus for staff or free group lunches. Providing a certificate of achievement or title promotion for mastering new tech may be appropriate. Giving some time off from other tasks to learn new workflows can reduce resistance rather than just adding it on to a regular workload. Office “huddles” going forward can include examples of benefits staff have observed or heard about from the adoption. There are quality improvement processes that engage the team — some that earn MOC-4 or CEU credits — that apply to making workflow changes and measuring them iteratively.

If technology takes over important aspects of the work of medical professionals, even if it is faster and/or more accurate, it may degrade clinical observational, interactional, and decision-making skills through lack of use. It may also remove the sense of self-efficacy that motivates professionals to endure onerous training and desire to enter the field. Using technology may reduce empathetic interactions that are basic to humanistic motivation, work satisfaction, and even community respect. Moral injury is already rampant in medicine from restrictions on freedom to do what we see as important for our patients. Technology has great potential and already is enhancing our ability to provide the best care for patients but the risks need to be watched for and ameliorated.

When technology automates comprehensive visit documentation that highlights priority and risk areas from patient input and individualizes decision support, it can facilitate the personalized care that we and our patients want to experience. We must not be so awed, intrigued, or wary of new technology to miss its benefits nor give up our good clinical judgment about the technology or about our patients.

Dr. Howard is assistant professor of pediatrics at The Johns Hopkins University School of Medicine, Baltimore, and creator of CHADIS. She had no other relevant disclosures. Dr. Howard’s contribution to this publication was as a paid expert to MDedge News. E-mail her at pdnews@mdedge.com.

We have all been using technology in our primary care practices for a long time but newer formats have been emerging so fast that our minds, much less our staff’s minds, may be spinning.

Our old friend the telephone, a time-soaking nemesis for scheduling, checking coverage, questions calls, prescribing, quick consults, and follow-up is being replaced by EHR portals and SMS for messaging (e.g. DoctorConnect, SimplePractice), drop-in televisits and patient education links on our websites (e.g. Schmitt Pediatric Care, Remedy Connect), and chatbots for scheduling (e.g. CHEC-UP). While time is saved, what is lost may be hearing the subtext of anxiety or misperceptions in parents’ voices that would change our advice and the empathetic human connection in conversations with our patients. A hybrid approach may be better.

The paper appointment book has been replaced by scheduling systems sometimes lacking in flexibility for double booking, sibling visits, and variable length or extremely valuable multi-professional visits. Allowing patients to book their own visits may place complex problems in inappropriate slots, so only allowing online requests for visits is safer. On the other hand, many of us can now squeeze in “same day” televisits (e.g. Blueberry Pediatrics), sometimes from outside our practice (e.g., zocdoc), to increase payments and even entice new patients to enroll.

Amazing advances in technology are being made in specialty care such as genetic modifications (CRISPR), immunotherapies (mRNA vaccines and AI drug design), robot-assisted surgery, and 3-D printing of body parts and prosthetics. Technology as treatment such as transcranial magnetic stimulation and vagal stimulation are finding value in psychiatry.

But beside being aware of and able to order such specialty technologies, innovations are now extending our senses in primary care such as amplified or visual stethoscopes, bedside ultrasound (e.g. Butterfly), remote visualization (oto-, endo-)scopes, photographic vision screens (e.g. iScreen) for skin lesion (VisualDx) and genetic syndrome facial recognition. We need to be sure that technologies are tested and calibrated for children and different racial groups and genders to provide safe and equitable care. Early adoption may not always be the best approach. Costs of technology, as usual, may limit access to these advanced care aids especially, as usual, in practices serving low income and rural communities.

Patients, especially younger parents and youth, now expect to participate and can directly benefit from technology as part of their health care. Validated parent or self-report screens (e.g. EHRs, Phreesia) can detect important issues early for more effective intervention. Such questionnaires typically provide a pass/fail result or score, but other delivery systems (e.g. CHADIS) include interpretation, assist patients/parents in setting visit priorities and health goals, and even chain results of one questionnaire to secondary screens to hone in on problems, sometimes obviating a time-consuming second visit. Patient-completed comprehensive questionnaires (e.g. Well Visit Planner, CHADIS) allow us time to use our skills to focus on concerns, education, and management rather than asking myriad routine questions. Some (e.g. CHADIS) even create visit documentation reducing our “pajama time” write ups (and burnout); automate repeated online measures to track progress; and use questionnaire results to trigger related patient-specific education and resources rather than the often-ignored generic EHR handouts.

Digital therapeutics such as apps for anxiety (e.g. Calm), depression (e.g. SparkRx, Cass), weight control (e.g. Noom, Lose it), fitness, or sleep tracking (e.g. Whoop) help educate and, in some cases, provide real-time feedback to personalize discovery of contributing factors in order to maintain motivation for positive health behavior change. Some video games improve ADHD symptoms (e.g. EndeavorRX). Virtual reality scenarios have been shown to desensitize those with PTSD and social anxiety or teach social skills to children with autism.

Systems that trigger resource listings (including apps) from screen results can help, but now with over 10,000 apps for mental health, knowing what to recommend for what conditions is a challenge for which ratings (e.g. MINDapps.org) can help. With few product reps visiting to tell us what’s new, we need to read critically about innovations, search the web, subscribe to the AAP SOAPM LISTSERV, visit exhibitors at professional meetings, and talk with peers.

All the digital data collected from health care technology, if assembled with privacy constraints and analyzed with advanced statistical methods, have the possibility, with or without inclusion of genomic data, to allow for more accurate diagnostic and treatment decision support. While AI can search widely for patterns, it needs to be “trained” on appropriate data to make correct conclusions. We are all aware that the history determines 85% of both diagnosis and treatment decisions, particularly in primary care where x-rays or lab tests are not often needed.

But history in EHR notes is often idiosyncratic, entered hours after the visit by the clinician, and does not include the information needed to define diagnostic or guideline criteria, even if the clinician knows and considered those criteria. EHR templates are presented blank and are onerous and time consuming for clinicians. In addition, individual patient barriers to care, preferences, and environmental or subjective concerns are infrequently documented even though they may make the biggest difference to adherence and/or outcomes.

Notes made from voice to text digital AI translation of the encounter (e.g. Nuance DAX) are even less likely to include diagnostic criteria as it would be inappropriate to speak these. To use EHR history data to train AI and to test efficacy of care using variations of guidelines, guideline-related data is needed from online patient entries in questionnaires that are transformed to fill in templates along with some structured choices for clinician entries forming visit notes (e.g. CHADIS). New apps to facilitate clinician documentation of guidelines (e.g. AvoMD) could streamline visits as well as help document guideline criteria. The resulting combination of guideline-relevant patient histories and objective data to test and iteratively refine guidelines will allow a process known as a “Learning Health System.”

Technology to collect this kind of data can allow for the aspirational American Academy of Pediatrics CHILD Registry to approach this goal. Population-level data can provide surveillance for illness, toxins, effects of climate change, social drivers of health, and even effects of technologies themselves such as social media and remote learning so that we can attempt to make the best choices for the future.

Clinicians, staff, and patients will need to develop trust in technology as it infiltrates all aspects of health care. Professionals need both evidence and experience to trust a technology, which takes time and effort. Disinformation in the media may reduce trust or evoke unwarranted trust, as we have all seen regarding vaccines. Clear and coherent public health messaging can help but is no longer a panacea for developing trust in health care. Our nonjudgmental listening and informed opinions are needed more than ever.

The biggest issues for new technology are likely to be the need for workflow adjustments, changing our habit patterns, training, and cost/benefit analyses. With today’s high staff churn, confusion and even chaos can ensue when adopting new technology.

Staff need to be part of the selection process, if at all possible, and discuss how roles and flow will need to change. Having one staff member be a champion and expert for new tech can move adoption to a shared process rather than imposing “one more thing.” It is crucial to discuss the benefits for patients and staff even if the change is required. Sometimes cost savings can include a bonus for staff or free group lunches. Providing a certificate of achievement or title promotion for mastering new tech may be appropriate. Giving some time off from other tasks to learn new workflows can reduce resistance rather than just adding it on to a regular workload. Office “huddles” going forward can include examples of benefits staff have observed or heard about from the adoption. There are quality improvement processes that engage the team — some that earn MOC-4 or CEU credits — that apply to making workflow changes and measuring them iteratively.

If technology takes over important aspects of the work of medical professionals, even if it is faster and/or more accurate, it may degrade clinical observational, interactional, and decision-making skills through lack of use. It may also remove the sense of self-efficacy that motivates professionals to endure onerous training and desire to enter the field. Using technology may reduce empathetic interactions that are basic to humanistic motivation, work satisfaction, and even community respect. Moral injury is already rampant in medicine from restrictions on freedom to do what we see as important for our patients. Technology has great potential and already is enhancing our ability to provide the best care for patients but the risks need to be watched for and ameliorated.

When technology automates comprehensive visit documentation that highlights priority and risk areas from patient input and individualizes decision support, it can facilitate the personalized care that we and our patients want to experience. We must not be so awed, intrigued, or wary of new technology to miss its benefits nor give up our good clinical judgment about the technology or about our patients.

Dr. Howard is assistant professor of pediatrics at The Johns Hopkins University School of Medicine, Baltimore, and creator of CHADIS. She had no other relevant disclosures. Dr. Howard’s contribution to this publication was as a paid expert to MDedge News. E-mail her at pdnews@mdedge.com.